pandas: replace non-empty rows in a column with a list

Question

I have a dataframe like the following (but longer) with some rows containing None values:

data = {'first Column':  ['she is', 'they are',NaN,'we are',NaN],
    'second Column ': ['my', 'her',NaN,'his',NaN],
    'third column': ['friend', 'brothers',NaN,'sisters',NaN]
    }

df = pd.DataFrame (data, columns = ['first Column','second Column','third column])

my_list= ['gold','silver','bronze']

I would like to replace every row in the 'third column' with a list if it does not contain none value, like this :

  desired output:
     first column   second column   third column
  0  she is          my             ['gold','silver','bronze']
  1  they are        her            ['gold','silver','bronze']
  2  NaN             NaN            NaN
  3  we are          his            ['gold','silver','bronze']
  4  NaN             NaN            NaN

I have tried np.where, but it does not select the desired rows

   np.where(df.loc[df['third column'] != 'NaN', [','.join(my_list)], df['third column']

Stef · Accepted Answer · 2020-06-24 13:22:10Z

2

df.loc[df['third column'].notna(),'third column']=[my_list]

Result:

  first Column second Column             third column
0       she is             my  [gold, silver, bronze]
1     they are            her  [gold, silver, bronze]
2          NaN            NaN                     NaN
3       we are            his  [gold, silver, bronze]
4          NaN            NaN                     NaN

PS: if you specifiy data as a dict with column names you don't need the columns argument in the dataframe constructor.

edited Jun 24, 2020 at 13:22

answered Jun 24, 2020 at 13:15

Stef

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