from copy import deepcopy # to copy old dataframes appropriately
# create 2 lists, first holds old dataframes and second holds modified ones
old_dfs_list, new_dfs_list = [pd.DataFrame[First], pd.DataFrame[Second]], []
# process old dfs one by one by iterating over old_dfs_list,
# copy, modify each and append it to list of new_dfs_list with same index as
# old df ... so old_dfs_list[1] is mapped to new_dfs_list[1]
for i in range[len[old_dfs_list]]:
# a deep copy prevent changing old dfs by reference
df_deep_copy = deepcopy[old_dfs_list[i]]
df_deep_copy['GDP'] *= 1.5
new_dfs_list.append[df_deep_copy]
print[old_dfs_list[0]] # to check that old dfs are not changed
print[new_dfs_list[0]]
Bạn cũng có thể thử từ điển thay vì danh sách để sử dụng tên bạn thích:
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Mục tiêu công thức
Trong Python, trong khi hoạt động trong danh sách, chúng ta có thể cần lưu trữ từng đầu ra vòng trong một khung dữ liệu với mỗi lần lặp.
Vì vậy, công thức này là một ví dụ ngắn về cách nối đầu ra cho vòng lặp trong khung dữ liệu gấu trúc. Bắt đầu nào.
Hãy đến gần hơn với giấc mơ trở thành một nhà khoa học dữ liệu với hơn 70 dự án ML từ đầu đến cuối đã được giải quyếtEnd-to-End ML Projects
Mục lục
- Mục tiêu công thức
- Trong Python, trong khi hoạt động trong danh sách, chúng ta có thể cần lưu trữ từng đầu ra vòng trong một khung dữ liệu với mỗi lần lặp.
- Vì vậy, công thức này là một ví dụ ngắn về cách nối đầu ra cho vòng lặp trong khung dữ liệu gấu trúc. Bắt đầu nào.
- Hãy đến gần hơn với giấc mơ trở thành một nhà khoa học dữ liệu với hơn 70 dự án ML từ đầu đến cuối đã được giải quyết
- Mục lục
- Bước 1 - Nhập thư viện
Trong Python, trong khi hoạt động trong danh sách, chúng ta có thể cần lưu trữ từng đầu ra vòng trong một khung dữ liệu với mỗi lần lặp.
import pandas as pd
Vì vậy, công thức này là một ví dụ ngắn về cách nối đầu ra cho vòng lặp trong khung dữ liệu gấu trúc. Bắt đầu nào.
Vì vậy, công thức này là một ví dụ ngắn về cách nối đầu ra cho vòng lặp trong khung dữ liệu gấu trúc. Bắt đầu nào.
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
Hãy đến gần hơn với giấc mơ trở thành một nhà khoa học dữ liệu với hơn 70 dự án ML từ đầu đến cuối đã được giải quyết
Hãy đến gần hơn với giấc mơ trở thành một nhà khoa học dữ liệu với hơn 70 dự án ML từ đầu đến cuối đã được giải quyết
for i in range[4,11]:
df=df.append[{'Table of 9':i*9,'Table of 10':i*10},ignore_index=True]
Mục lục
Mục lục
print['df\n',df]
Bước 1 - Nhập thư viện
Bước 1 - Nhập thư viện
Bước 2 - Thiết lập dữ liệu
Scroll down to the ipython notebook below to see the output.
Xem thảo luận
Cải thiện bài viết
Lưu bài viết
Xem thảo luận
Cải thiện bài viết
Lưu bài viết
Đọc
Python3
Bàn luận
Thêm một cột mới trong một DataFrame đã được tạo là khá dễ dàng. Thêm một cột mới thực sự được yêu cầu để xử lý dữ liệu của DataFrame được tạo trước đó. Với mục đích đó, chúng tôi có thể xử lý dữ liệu hiện có và tạo một cột riêng để lưu trữ dữ liệu. Cách đơn giản nhất để thêm một cột mới cùng với dữ liệu là bằng cách tạo một cột mới và gán các giá trị mới cho nó. Ví dụ:
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Scroll down to the ipython notebook below to see the output.
7First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail3
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail5
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail9
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail2
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail3
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail5
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Scroll down to the ipython notebook below to see the output.
8import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
import pandas as pd
3
import pandas as pd
4
import pandas as pd
5
import pandas as pd
6
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7
import pandas as pd
9
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
0
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
1
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
0
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
1
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
0
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
1
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
0
import pandas as pd
9
import pandas as pd
6
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
9
Output:
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Example#2
Python3
Bàn luận
Thêm một cột mới trong một DataFrame đã được tạo là khá dễ dàng. Thêm một cột mới thực sự được yêu cầu để xử lý dữ liệu của DataFrame được tạo trước đó. Với mục đích đó, chúng tôi có thể xử lý dữ liệu hiện có và tạo một cột riêng để lưu trữ dữ liệu. Cách đơn giản nhất để thêm một cột mới cùng với dữ liệu là bằng cách tạo một cột mới và gán các giá trị mới cho nó. Ví dụ:
Scroll down to the ipython notebook below to see the output.
7Scroll down to the ipython notebook below to see the output.
8import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail0
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail2
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail4
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail6
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail8
Scroll down to the ipython notebook below to see the output.
6Scroll down to the ipython notebook below to see the output.
7First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail3
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail5
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail9
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail2
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail3
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail5
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Scroll down to the ipython notebook below to see the output.
8import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail1
import pandas as pd
3import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
Output:
First_name Last_name Marks Result 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail
Example#3
Chúng tôi cũng có thể sử dụng danh sách hiểu để tạo một cột mới. & NBSP;
Python3
import pandas as pd
4
import pandas as pd
5
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
import pandas as pd
datadicts_dict = {
'first' :{'GDP':[200,175,150,100]},
'second':{'GDP':[550,200,235,50]},
'third' :{'GDP':[600,400,520,100, 800]}
}
# Create datasets and store it in a python dictionary
old_dfs_dict, new_dfs_dict = {}, {} # initialize 2 dicts to hold original and modified dataframes
# process datasets one by one by iterating over datadicts_dict,
# convert to df save it in old_dfs_dict with same name as the key
# copy, modify each and put it in new_dfs_dict with same key
# so dataset of key 'first' in datadicts_dict is saved as old_dfs_dict['first']
# modified and mapped to new_dfs_dict['first']
for dataset_name, data_dict in datadicts_dict.items[]:
old_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}]
new_dfs_dict[dataset_name] = pd.DataFrame[{'GDP':data_dict['GDP']}] * 1.5
print[old_dfs_dict['third']] # to check that old dfs are not changed
print[new_dfs_dict['third']]
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail7______
df= pd.DataFrame[{'Table of 9': [9,18,27],
'Table of 10': [10,20,30]}]
9
Output:
First_name Last_name Marks Results 0 Ram Kumar 12 Fail 1 Mohan Sharma 52 Pass 2 Tina Ali 36 Pass 3 Jeetu Gandhi 85 Pass 4 Meera Kumari 23 Fail
Làm thế nào để bạn lưu một khung dữ liệu bên trong một vòng lặp?
Bước 1 - Nhập thư viện. Nhập GANDAS dưới dạng PD. ....
Bước 2 - Thiết lập dữ liệu. df = pd.dataFrame [{'Bảng 9': [9,18,27], 'Bảng 10': [10,20,30]}] ....
Bước 3 - Bấp tới DataFrame trong A For Loop. Đối với i trong phạm vi [4,11]: df = df.Append [{'Bảng 9': i*9, 'Bảng 10': i*10}, bỏ qua_index = true] ...
Bước 4 - Kết quả in. in ['df \ n', df].
Bạn có thể lặp lại một khung dữ liệu trong Python không?
Bạn có thể lặp qua một DataFrame của Pandas, cho mỗi hàng cột từng hàng..
Làm thế nào để tôi lưu một khung dữ liệu gấu trúc trong Python?
Trong bài viết này, chúng tôi sẽ tìm hiểu làm thế nào chúng tôi có thể xuất một bản dữ liệu gấu trúc sang tệp CSV bằng cách sử dụng phương thức gấu trúc to_csv [].Theo mặc định, phương thức CSV [] xuất DataFrame sang tệp CSV với chỉ mục hàng dưới dạng cột đầu tiên và dấu phẩy là dấu phân cách.by using the Pandas to_csv[] method. By default, the to csv[] method exports DataFrame to a CSV file with row index as the first column and comma as the delimiter.
Bạn có thể chạy một vòng lặp cho DataFrame không?
DataFrame được lặp lại cho vòng lặp vì nó là, tên cột được trả về.Bạn có thể lặp lại các cột và hàng gấu trúc.DataFrame với các phương thức iterItems [], iterrows [] và itertuples []. as it is, column names are returned. You can iterate over columns and rows of pandas. DataFrame with the iteritems[] , iterrows[] , and itertuples[] methods.