Pandas-将列添加到基于其中一列的Dict的DataFrame中

Question

I have the pandas.DataFrame below:

One of the columns from the Dataframe, pontos , holds a dict for each of the rows.

What I want to do is add one column to the DataFrame for each key from this dict. So the new columns would be, in this example: rodada , mes , etc, and for each row, these columns would be populated with the respective value from the dict.

So far I've tried the following for one of the keys:

df_times["rodada"] = [df_times["pontos"].get('rodada') for d in df_times["pontos"]]

However, as a result I'm getting a new column rodada filled with None values:

Any hints on what I'm doing wrong?

Answer 1

You can create a new dataframe and concat it to the current one like:

Code:

df2 = pd.concat([df, pd.DataFrame(list(df.pontos))], axis=1)

Test Code:

import pandas as pd

df = pd.DataFrame([
    ['A', dict(col1='1', col2='2')],
    ['B', dict(col1='3', col2='4')],
], columns=['X', 'D'])

print(df)

df2 = pd.concat([df, pd.DataFrame(list(df.D))], axis=1)
print(df2)

Results:

   X                           D
0  A  {'col2': '2', 'col1': '1'}
1  B  {'col2': '4', 'col1': '3'}

   X                           D col1 col2
0  A  {'col2': '2', 'col1': '1'}    1    2
1  B  {'col2': '4', 'col1': '3'}    3    4

Answer 2

You just need a slight change in your comprehension to extract that data.

It should be:

df_times["rodada"] = [d.get('rodada') for d in df_times["pontos"]]

You want the values of the dictionary key 'rodada' to be the basis of your new column. So you iterate over those dictionary entries in the loop- in other words, d, and then extract the value by key to make the new column.

Answer 3

您还可以使用join和pandas apply功能：

df=df.join(df['pontos'].apply(pd.Series))