Hướng dẫn how do i find the number of columns in a csv file in python? - làm cách nào để tìm số cột trong tệp csv trong python?

Chương trình của tôi cần đọc các tệp CSV có thể có 1,2 hoặc 3 cột và nó cần sửa đổi hành vi của nó cho phù hợp. Có cách nào đơn giản để kiểm tra số lượng cột mà không "tiêu thụ" một hàng trước khi trình lặp chạy không? Mã sau là thanh lịch nhất tôi có thể quản lý, nhưng tôi muốn chạy kiểm tra trước khi vòng lặp bắt đầu:

import csv
f = 'testfile.csv'
d = '\t'

reader = csv.reader(f,delimiter=d)
for row in reader:
    if reader.line_num == 1: fields = len(row)
    if len(row) != fields:
        raise CSVError("Number of fields should be %s: %s" % (fields,str(row)))
    if fields == 1:
        pass
    elif fields == 2:
        pass
    elif fields == 3:
        pass
    else:
        raise CSVError("Too many columns in input file.")

Chỉnh sửa: Tôi nên bao gồm thêm thông tin về dữ liệu của tôi. Nếu chỉ có một lĩnh vực, nó phải chứa một tên trong ký hiệu khoa học. Nếu có hai trường, phần thứ nhất phải chứa một tên và mã liên kết thứ hai. Nếu có ba trường, trường bổ sung chứa một lá cờ chỉ định liệu tên hiện có hợp lệ hay không. Do đó, nếu bất kỳ hàng nào có 1, 2 hoặc 3 cột, tất cả phải có cùng. I should have included more information about my data. If there is only one field, it must contain a name in scientific notation. If there are two fields, the first must contain a name, and the second a linking code. If there are three fields, the additional field contains a flag which specifies whether the name is currently valid. Therefore if any row has 1, 2 or 3 columns, all must have the same.

Làm cách nào để tìm số lượng hàng và cột trong tệp CSV trong Python?

Để có được số lượng hàng và các cột, chúng ta có thể sử dụng hàm Len (df.axes []) trong Python.

Là một phần của quy trình nếu bạn đang thao túng dữ liệu này, bạn cần đảm bảo rằng tất cả các điều đó đã được tải mà không bị lỗi.

Với suy nghĩ này, chúng tôi sẽ tìm cách giúp bạn với một nhiệm vụ tự động hóa có thể để đảm bảo rằng:

(A) Tất cả các hàng và cột được tổng cộng khi tải tệp CSV.

(B) Là một phần của quy trình, nếu cùng một bộ dữ liệu được xuất, tổng số xuất khẩu có thể được tính.

(C) Điều này đảm bảo rằng tất cả các hàng và cột cần thiết luôn có sẵn.

Mã python sẽ giúp bạn với điều này

Vì vậy, trong mã dưới đây, có một số điều cần xem xét.

Hãy xem tệp CSV mà chúng ta sẽ đọc trong:

Tổng cộng có mười hàng với dữ liệu. Hàng trên cùng không được bao gồm trong số đếm vì nó được coi là một hàng tiêu đề. Ngoài ra còn có bảy cột.

Bit đầu tiên này chỉ đọc trong dữ liệu và nó tự động bỏ qua hàng tiêu đề.

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Tiếp theo, nó tạo ra hai biến đếm không có hàng và cột và in chúng ra.

Lưu ý rằng nó đã sử dụng các df.axes để nói với Python không nhìn vào các ô riêng lẻ.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Và mang tất cả lại với nhau

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

Tóm lại, điều này sẽ rất hữu ích nếu bạn đang cố gắng giảm lượng nỗ lực thủ công trong việc kiểm tra dân số của một tập tin.

Kết quả là nó sẽ giúp:

(A) Các tập lệnh xử lý dữ liệu không loại bỏ các hàng hoặc cột một cách không cần thiết.

.

(C) Nhật ký điều khiển - Cơ sở dữ liệu có thể lưu trữ dữ liệu này để cho thấy những gì được xử lý là chính xác.

(D) Khi chạy tự động phải được tạm dừng, điều này có thể giúp xác định vấn đề và sau đó nhanh chóng khắc phục.

.

Đây là một bài viết khác bạn nên đọc!

Cách thay đổi các tiêu đề trên tệp CSV

Mở tệp CSV trong Python bằng hàm mở (tệp) với tệp dưới dạng tệp CSV ..

Example:

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

Tạo đầu đọc CSV bằng cách gọi hàm CSV. ....

Nhận đại diện danh sách của tệp CSV bằng cách gọi danh sách (( *args)) với *args làm trình đọc từ bước trước ..

Python3

import

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

6
4

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

24

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

24

6
6

‘

6
6

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
6

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import3import4

import3import6import7__

import3import6

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Đầu ra: & nbsp; 

Đếm số lượng hàng và cột của dataFrame bằng hàm thông tin ()

Chức năng pandas dataFrame.info () được sử dụng để có một bản tóm tắt ngắn gọn về DataFrame. Ở đây chúng ta có thể thấy rằng chúng ta nhận được một chi tiết tóm tắt về DataFrame chứa số lượng hàng và cột.

Python3

import

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Các

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import3

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Output:

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

Đếm số lượng hàng và cột của dataFrame bằng hàm len ().

Hàm Len () trả về các hàng độ dài của DataFrame, chúng ta có thể lọc một số cột bằng cách sử dụng DF.Columns để lấy số lượng cột.

Python3

import

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Các

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import3import6

6
6

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import3import6

6
6

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:

6
4

Đếm số lượng hàng và cột của dataFrame bằng hàm len ().

Hàm Len () trả về các hàng độ dài của DataFrame, chúng ta có thể lọc một số cột bằng cách sử dụng DF.Columns để lấy số lượng cột.df.shape.

Python3

Đếm số lượng hàng và cột của DataFrame bằng hình dạng.

Ở đây, chúng tôi sẽ thử một cách tiếp cận khác để tính toán các hàng và cột của khung dữ liệu của tệp CSV đã nhập và đếm các hàng và cột bằng DF.Shape.

Đầu ra:

Python3

import

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Các

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import3

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

Output:

24

Đếm số lượng hàng và cột của dataFrame bằng hàm len ().

Hàm Len () trả về các hàng độ dài của DataFrame, chúng ta có thể lọc một số cột bằng cách sử dụng DF.Columns để lấy số lượng cột.

Python3

import

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

24

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

RangeIndex: 6 entries, 0 to 5
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype 
---  ------         --------------  ----- 
 0   name           6 non-null      object
 1   score          6 non-null      int64 
 2   age            6 non-null      int64 
 3   qualify_label  6 non-null      object
dtypes: int64(2), object(2)
memory usage: 320.0+ bytes
None

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

Input: {'name':          ['Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura'],
        'score':         [98, 80, 60, 85, 49, 92],
        'age':           [20, 25, 22, 24, 21, 20],
        'qualify_label': ['yes', 'yes', 'no','yes', 'no', 'yes']}

Output: Number of Rows: 6
        Number of Columns: 4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.


Output with first line used:
Number of Rows: 10
Number of Columns: 7

6
4

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 1 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Các

import3

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

6
6

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

import3import6

6
6

import pandas as pd

df = pd.read_csv("csv_import.csv") #===> reads in all the rows, but skips the first one as it is a header.

total_rows=len(df.axes[0]) #===> Axes of 0 is for a row
total_cols=len(df.axes[1]) #===> Axes of 0 is for a column
print("Number of Rows: "+str(total_rows))
print("Number of Columns: "+str(total_cols))

Output:
Number of Rows: 10
Number of Columns: 7

Output:

6
6

Làm cách nào để đếm các cột trong tệp CSV?

Làm cách nào để tìm số lượng hàng và cột trong tệp CSV trong Python?

Làm cách nào để thấy tất cả các cột trong tệp CSV trong Python?

Làm thế nào để bạn đếm các phần tử trong tệp CSV trong Python?