programming python Horizontal bar chart Bar chart Python Plt stacked bar Bar chart matplotlib Bar in matplotlib Pandas plot bar

Hướng dẫn how do i show the bar in python? - làm cách nào để hiển thị thanh trong python?

Biểu đồ thanh hoặc biểu đồ thanh là biểu đồ hoặc biểu đồ trình bày dữ liệu phân loại với các thanh hình chữ nhật có chiều cao hoặc chiều dài tỷ lệ thuận với các giá trị mà chúng đại diện. Các thanh có thể được vẽ theo chiều dọc hoặc chiều ngang.

Một biểu đồ thanh hiển thị so sánh giữa các danh mục riêng biệt. Một trục của biểu đồ cho thấy các loại cụ thể được so sánh và trục khác đại diện cho giá trị đo được.

API Matplotlib cung cấp hàm thanh [] có thể được sử dụng trong kiểu MATLAB sử dụng cũng như API hướng đối tượng. Chữ ký của hàm thanh [] được sử dụng với đối tượng trục như sau -bar[] function that can be used in the MATLAB style use as well as object oriented API. The signature of bar[] function to be used with axes object is as follows −

ax.bar[x, height, width, bottom, align]

Hàm tạo ra một biểu đồ thanh với hình chữ nhật ràng buộc có kích thước [x −width = 2; x + width = 2; dưới cùng + chiều cao].

Các tham số cho hàm là -

xTrình tự vô hướng đại diện cho tọa độ X của các thanh. Căn chỉnh điều khiển nếu X là trung tâm thanh [mặc định] hoặc cạnh trái.
Chiều caovô hướng hoặc chuỗi vô hướng biểu thị [các] chiều cao của các thanh.
bề rộngvô hướng hoặc giống như mảng, tùy chọn. chiều rộng của các thanh mặc định 0.8
đáyvô hướng hoặc giống như mảng, tùy chọn. Các tọa độ y của các thanh mặc định không có.
căn chỉnh{‘Center,‘ Edge,}, tùy chọn, mặc định ‘trung tâm

Hàm trả về một đối tượng container matplotlib với tất cả các thanh.

Sau đây là một ví dụ đơn giản về lô thanh matplotlib. Nó cho thấy số lượng sinh viên đăng ký cho các khóa học khác nhau được cung cấp tại một học viện.

import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]

Khi so sánh một số đại lượng và khi thay đổi một biến, chúng ta có thể muốn một biểu đồ thanh nơi chúng ta có các thanh có một màu cho một giá trị số lượng.

Chúng ta có thể vẽ nhiều biểu đồ thanh bằng cách chơi với độ dày và vị trí của các thanh. Biến dữ liệu chứa ba loạt bốn giá trị. Kịch bản sau đây sẽ hiển thị ba biểu đồ thanh của bốn thanh. Các thanh sẽ có độ dày 0,25 đơn vị. Mỗi biểu đồ thanh sẽ được thay đổi 0,25 đơn vị từ số trước. Đối tượng dữ liệu là một đa số có chứa số lượng sinh viên được thông qua trong ba chi nhánh của một trường đại học kỹ thuật trong bốn năm qua.

import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]

Các bảng xếp hạng thanh xếp chồng xếp các thanh đại diện cho các nhóm khác nhau trên nhau. Chiều cao của thanh kết quả cho thấy kết quả kết hợp của các nhóm.

Tham số dưới cùng tùy chọn của hàm pyplot.bar [] cho phép bạn chỉ định giá trị bắt đầu cho thanh. Thay vì chạy từ 0 đến một giá trị, nó sẽ đi từ dưới cùng đến giá trị. Cuộc gọi đầu tiên đến pyplot.bar [] vẽ các thanh màu xanh. Cuộc gọi thứ hai đến pyplot.bar [] vẽ các thanh màu đỏ, với phần dưới của các thanh màu xanh nằm trên đỉnh của các thanh màu đỏ.pyplot.bar[] function allows you to specify a starting value for a bar. Instead of running from zero to a value, it will go from the bottom to the value. The first call to pyplot.bar[] plots the blue bars. The second call to pyplot.bar[] plots the red bars, with the bottom of the blue bars being at the top of the red bars.

import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]

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    Tạo một lô thanh

    API matplotlib trong python cung cấp hàm thanh [] có thể được sử dụng trong sử dụng kiểu MATLAB hoặc như một API hướng đối tượng. Cú pháp của hàm thanh [] được sử dụng với các trục như sau:-matplotlib API in Python provides the bar[] function which can be used in MATLAB style use or as an object-oriented API. The syntax of the bar[] function to be used with the axes is as follows:-

    plt.bar[x, height, width, bottom, align]

    Hàm tạo ra một biểu đồ thanh giới hạn với một hình chữ nhật tùy thuộc vào các tham số đã cho. Sau đây là một ví dụ đơn giản về cốt truyện thanh, đại diện cho số lượng sinh viên đăng ký vào các khóa học khác nhau của một học viện. & NBSP; & NBSP;
     

    Python3

    import numpy as np

    import matplotlib.pyplot as plt

    data 

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    1
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    3
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    4
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    6
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    3
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    8
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5__

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    3
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    7
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    8

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    9____10 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    1
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    2

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    3
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    1
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    6

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    7
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    9____10 
    plt.bar[x, height, width, bottom, align]
    1
    plt.bar[x, height, width, bottom, align]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    4445

    plt.bar[x, height, width, bottom, align]
    6
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    plt.bar[x, height, width, bottom, align]
    8
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    3

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4import1
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 import3import4

    import5import6import4

    import8import9import4

    numpy as np1numpy as np2import4

    numpy as np4

    Output-   
     

    Ở đây plt.bar [các khóa học, giá trị, color = xông maroon,] được sử dụng để chỉ định rằng biểu đồ thanh sẽ được vẽ bằng cách sử dụng cột các khóa học làm trục x và các giá trị là trục y. Thuộc tính màu được sử dụng để đặt màu của các thanh [maroon trong trường hợp này] .plt.xlabel [các khóa học được cung cấp] và plt.ylabel [sinh viên đã đăng ký] được sử dụng để dán nhãn các trục tương ứng.plt.title [ ] được sử dụng để tạo một tiêu đề cho biểu đồ.plt.show [] được sử dụng để hiển thị biểu đồ làm đầu ra bằng cách sử dụng các lệnh trước. & nbsp;
     

    Tùy chỉnh lô thanh

    Python3

    import numpy as np6

    numpy as np7 numpy as np8import import0

    data ____10 import3import4import4

    import6

    import7

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 import9

    matplotlib.pyplot as plt0

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 matplotlib.pyplot as plt2matplotlib.pyplot as plt3matplotlib.pyplot as plt4______8555554

    matplotlib.pyplot as plt7

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 matplotlib.pyplot as plt2data 0matplotlib.pyplot as plt4______8555554

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    7
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    9
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    plt.bar[x, height, width, bottom, align]
    1
    plt.bar[x, height, width, bottom, align]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    01
    plt.bar[x, height, width, bottom, align]
    5

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    03
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    3
    plt.bar[x, height, width, bottom, align]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    07
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    3
    plt.bar[x, height, width, bottom, align]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    11

    numpy as np4

    Output: 
     

    Nó được quan sát trong biểu đồ thanh trên rằng các ve trục X chồng chéo lẫn nhau do đó không thể nhìn thấy đúng. Do đó, bằng cách xoay các ve trục x, nó có thể được nhìn thấy rõ ràng. Đó là lý do tại sao cần tùy chỉnh trong biểu đồ thanh là bắt buộc.

    Python3

    import numpy as np6

    numpy as np7 numpy as np8import import0

    data ____10 import3import4import4

    import6

    import7

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 import9

    matplotlib.pyplot as plt0

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 matplotlib.pyplot as plt2matplotlib.pyplot as plt3matplotlib.pyplot as plt4______8555554

    matplotlib.pyplot as plt7

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 matplotlib.pyplot as plt2data 0matplotlib.pyplot as plt4______8555554

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    7
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    9
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    plt.bar[x, height, width, bottom, align]
    1
    plt.bar[x, height, width, bottom, align]
    2
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    01
    plt.bar[x, height, width, bottom, align]
    5

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    51

    Nó được quan sát trong biểu đồ thanh trên rằng các ve trục X chồng chéo lẫn nhau do đó không thể nhìn thấy đúng. Do đó, bằng cách xoay các ve trục x, nó có thể được nhìn thấy rõ ràng. Đó là lý do tại sao cần tùy chỉnh trong biểu đồ thanh là bắt buộc.

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    64
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    65
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    66import4

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    68
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    69import4

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    71
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    69import4

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    42
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    44
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    plt.bar[x, height, width, bottom, align]
    1
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    47
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    49
    plt.bar[x, height, width, bottom, align]
    5

    Is

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    plt.bar[x, height, width, bottom, align]
    4import4

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    78
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    plt.bar[x, height, width, bottom, align]
    2import4

    ‘

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    02

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    90
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0__192

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    64
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    08
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    00
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    11
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    95
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    3

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    15
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    16
    plt.bar[x, height, width, bottom, align]
    1
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    18
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    19
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    20
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    21

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    98
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    00import4

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    15
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    31
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    87import4

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    35
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    36
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    3

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    15
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    39
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    60
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    42

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    54 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    06

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    53
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    31
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    87
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    57
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    62
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    60
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    58
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    3

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    15
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    23
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    plt.bar[x, height, width, bottom, align]
    2
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    26____10
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    28
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    3

    numpy as np4

    Output: 
     

    Các
     

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    53
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    98
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    67import4

    Có nhiều tùy chỉnh khác có sẵn cho các lô thanh. & NBSP;

    Python3

    import numpy as np

    import matplotlib.pyplot as plt

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    76

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    7
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    444____10 ____41matplotlib.pyplot as plt5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    844____45

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    86
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    55matplotlib.pyplot as plt5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    222215
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    93
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    844
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5__297

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    99
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    55
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    02
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    47
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    4441515____42

    Is

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    25
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    27
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    28
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    29

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    30
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    32
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    39
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    32
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    36__

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    48
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0___

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    55
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    87
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    58
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    60import4

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    62
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    64
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    51
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    53

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    55
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    87
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    58
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    74import4

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    76
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    78
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    51
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    53

    Các

    import5___

    Các

    plt.bar[x, height, width, bottom, align]
    08
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52 
    plt.bar[x, height, width, bottom, align]
    12
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    54

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    4
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    55
    plt.bar[x, height, width, bottom, align]
    20
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    22
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    24
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    26
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    28
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    11

    plt.bar[x, height, width, bottom, align]
    30

    numpy as np4

    Output: 
     

    Cốt truyện xếp chồng

    Các lô thanh xếp chồng lên nhau đại diện cho các nhóm khác nhau trên đầu nhau. Chiều cao của thanh phụ thuộc vào chiều cao kết quả của sự kết hợp kết quả của các nhóm. Nó đi từ dưới cùng đến giá trị thay vì đi từ 0 đến giá trị. Lô thanh sau đây đại diện cho sự đóng góp của các chàng trai và cô gái trong đội. & NBSP;
     

    Python3

    import numpy as np

    import matplotlib.pyplot as plt

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    76

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    7
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    444____10 ____41matplotlib.pyplot as plt5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    844____45

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    86
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    55matplotlib.pyplot as plt5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    222215
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    93
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    844
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5__297

    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    99
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    55
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    02
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    47
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    4441515____42

    Is

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    25
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    27
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    28
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    29

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    30
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    32
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    39
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    32
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    09 
    import numpy as np
import matplotlib.pyplot as plt
data = [[30, 25, 50, 20],
[40, 23, 51, 17],
[35, 22, 45, 19]]
X = np.arange[4]
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[X + 0.00, data[0], color = 'b', width = 0.25]
ax.bar[X + 0.25, data[1], color = 'g', width = 0.25]
ax.bar[X + 0.50, data[2], color = 'r', width = 0.25]
    74
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    52 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    36__

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    48
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0___

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    62
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    64
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    51
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    53

    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    76
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    78
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    51
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    0 
    import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = [20, 35, 30, 35, 27]
womenMeans = [25, 32, 34, 20, 25]
ind = np.arange[N] # the x locations for the groups
width = 0.35
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
ax.bar[ind, menMeans, width, color='r']
ax.bar[ind, womenMeans, width,bottom=menMeans, color='b']
ax.set_ylabel['Scores']
ax.set_title['Scores by group and gender']
ax.set_xticks[ind, ['G1', 'G2', 'G3', 'G4', 'G5']]
ax.set_yticks[np.arange[0, 81, 10]]
ax.legend[labels=['Men', 'Women']]
plt.show[]
    53

    import8import21import4

    numpy as np1import24import4

    import26import27

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5import29
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5import31
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5import33
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5import35
    plt.bar[x, height, width, bottom, align]
    5

    import37

    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    04
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5import40
    import matplotlib.pyplot as plt
fig = plt.figure[]
ax = fig.add_axes[[0,0,1,1]]
langs = ['C', 'C++', 'Java', 'Python', 'PHP']
students = [23,17,35,29,12]
ax.bar[langs,students]
plt.show[]
    5
    plt.bar[x, height, width, bottom, align]
    2
    plt.bar[x, height, width, bottom, align]
    5

    Các

    numpy as np4

    Output-   
     


    Làm cách nào để hiển thị một biểu đồ thanh trong Python?

    Các bước để tạo biểu đồ thanh trong Python bằng matplotlib..
    Bước 1: Cài đặt gói matplotlib. ....
    Bước 2: Thu thập dữ liệu cho biểu đồ thanh. ....
    Bước 3: Chụp dữ liệu trong Python. ....
    Bước 4: Tạo biểu đồ thanh trong Python bằng Matplotlib ..

    Làm thế nào để bạn hiển thị giá trị của biểu đồ thanh?

    Bạn có thể sử dụng các giá trị ô làm nhãn dữ liệu cho biểu đồ của bạn.Nhấp chuột phải vào chuỗi dữ liệu hoặc nhãn dữ liệu để hiển thị nhiều dữ liệu hơn, sau đó nhấp vào định dạng Nhãn dữ liệu. Bấm vào các tùy chọn nhãn và bên dưới Nhãn chứa, chọn Hộp kiểm Giá từ ô.Right-click the data series or data label to display more data for, and then click Format Data Labels. Click Label Options and under Label Contains, select the Values From Cells checkbox.

    Thanh trong Python là gì?

    Biểu đồ thanh hoặc biểu đồ thanh là một biểu đồ đại diện cho danh mục dữ liệu với các thanh hình chữ nhật có độ dài và độ cao tỷ lệ thuận với các giá trị mà chúng đại diện.Các ô thanh có thể được vẽ theo chiều ngang hoặc chiều dọc.Một biểu đồ thanh mô tả các so sánh giữa các loại riêng biệt.a graph that represents the category of data with rectangular bars with lengths and heights that is proportional to the values which they represent. The bar plots can be plotted horizontally or vertically. A bar chart describes the comparisons between the discrete categories.

    Làm thế nào để bạn thêm một thanh vào một nhãn trong Python?

    Lập danh sách các năm ..
    Lập danh sách các quần thể trong năm đó ..
    Nhận số lượng nhãn bằng NP.....
    Đặt chiều rộng của các thanh ..
    Tạo các biến FIG và AX bằng phương thức Subplots [], trong đó NROW và NCOL mặc định là 1 ..
    Đặt nhãn trục y của hình bằng set_ylabel [] ..

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