19

I apply some functions and generate a new column values to a existing column of Pandas dataframe. However df['col1'] = new_list does not work to assign new list to the column. Is it the wrong way and what is the accurate way to apply such operation ?

erogol
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    `df` is a dictionary ? Are you receiving an error or what? Post more details please. –  Nov 04 '13 at 23:08
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    I guess `df` is a Pandas' `DataFrame`, as the title and text of the question suggests. – piokuc Nov 04 '13 at 23:21
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    When you say it "doesn't work" could you clarify what exactly isn't working, e.g. an example and the full stacktrace. It looks like it should work. – Andy Hayden Nov 04 '13 at 23:58
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    Yes it should've worked could you post some sample data and the errors – EdChum Nov 05 '13 at 00:00

3 Answers3

19

It should work if length of the list is equal to the number of rows in the DataFrame

>>> df = pd.DataFrame({'A':[1,2,3], 'B':[4,5,6]})
>>> df['C'] = [10,20,30]
>>> df
   A  B   C
0  1  4  10
1  2  5  20
2  3  6  30

If your list is shorter or longer than DataFrame, then you'll receive an error Length of values does not match length of index.

Roman Pekar
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2

I think this question is looking for something like this.

new_list = [1,2,3]

    col1
0  [1,2,3]
1  [1,2,3]
2  [1,2,3]

And I think I found the answer here:

how to assign an entire list to each row of a pandas dataframe

codenewbie
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  • You can improve your answer by adding one or more solutions from the linked page. For example: `df['col1'] = [new_list] * len(df)` – Dmitriy Work Jun 30 '22 at 09:09
0

I have prepared some more as op asked, I just didn't want to omit /cut some useful tips (still related to the adding a list as a column), hope helps someone.

import pandas as pd
from tabulate import tabulate  
# Module tabulate is optional just for pretty printing of the Data Frame / need install if not installed i.e:  pip install tabulate


# Table1 (in terminal screen): Add a list during creation of the Data Frame #

list1 = ['apple', 'banana', 'orange', 'avocado', 'melon', 'papaya']
df1 = pd.DataFrame(list1,columns = ['Fruits'])

print(tabulate(df1,headers='keys',tablefmt='pretty'),'\n')     # ==> Or just print(df1)  little messy


# Table2 : Add a list as a new column to an existing Data Frame #

list2 = ['3$','4$','2.5$','10$','5$','12$']
df1['Prices'] = list2

print(tabulate(df1,headers='keys',tablefmt='pretty'),'\n')

# Table3 : Small Trick for part4 : Add only the column name with some dummy data #

df1['Amount(Kg)'] = '0'

print(tabulate(df1,headers='keys',tablefmt='pretty'),'\n')

# Table4 : Now you can assign your existing list to an existing column  #

list3 = [100,90,80,70,60,50]
df1['Amount(Kg)'] = list3

print(tabulate(df1,headers='keys',tablefmt='pretty'),'\n')

Will generate the following output :

+---+---------+
|   | Fruits  |
+---+---------+
| 0 |  apple  |
| 1 | banana  |
| 2 | orange  |
| 3 | avocado |
| 4 |  melon  |
| 5 | papaya  |
+---+---------+

+---+---------+--------+
|   | Fruits  | Prices |
+---+---------+--------+
| 0 |  apple  |   3$   |
| 1 | banana  |   4$   |
| 2 | orange  |  2.5$  |
| 3 | avocado |  10$   |
| 4 |  melon  |   5$   |
| 5 | papaya  |  12$   |
+---+---------+--------+

+---+---------+--------+------------+
|   | Fruits  | Prices | Amount(Kg) |
+---+---------+--------+------------+
| 0 |  apple  |   3$   |     0      |
| 1 | banana  |   4$   |     0      |
| 2 | orange  |  2.5$  |     0      |
| 3 | avocado |  10$   |     0      |
| 4 |  melon  |   5$   |     0      |
| 5 | papaya  |  12$   |     0      |
+---+---------+--------+------------+

+---+---------+--------+------------+
|   | Fruits  | Prices | Amount(Kg) |
+---+---------+--------+------------+
| 0 |  apple  |   3$   |    100     |
| 1 | banana  |   4$   |     90     |
| 2 | orange  |  2.5$  |     80     |
| 3 | avocado |  10$   |     70     |
| 4 |  melon  |   5$   |     60     |
| 5 | papaya  |  12$   |     50     |
+---+---------+--------+------------+

If the op had added a line like in Section 3 above, his code would also work. But As I said I wanted you to see and visualize other steps too.

df['col1'] = '0'
df['col1'] = new_list
everyt4u
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