Pandas: Update Column Values from Another Column If Criteria

Updating a column in a Pandas DataFrame based on a condition of another column

If you know your colors before-hand, you could use masking with DataFrame.where and str.join to get this done.

v = pd.DataFrame(
     np.repeat([['red;', 'blue;']], len(df), axis=0), 
     columns=df.columns, 
     index=df.index
) 
df['msg'] = v.where(df.applymap(len) > 0, '').agg(''.join, axis=1)

df
   A  B        msg
0  x  x  red;blue;
1     x      blue;
2  x          red;
3              

assign one column value to another column based on condition in pandas

Based on the answers to this similar question, you can do the following:

• Using np.where:

  df['column2'] = np.where((df['column2'] == 'Null') | (df['column2'] == 0), df['column1'], df['column2'])
  

• Instead, using only pandas and Python:

  df['column2'][(df['column2'] == 0) | (df['column2'] == 'Null')] = df['column1']
  

update pandas dataframe column with value from another dataframe with condition

Let's try map instead:

to_map = df2[df2.week==1].set_index('team')['score']

to_update = df1.week==1

df1.loc[to_update, 'score1'] = df1.loc[to_update,'team1'].map(to_map)
df1.loc[to_update, 'score2'] = df1.loc[to_update,'team2'].map(to_map)

Output:

   week team1 team2 score1 score2
0     1    aa    hh     24     10
1     1    bb    ii     27      3
2     2    cc    jj              
3     1    dd    kk      7     20
4     1    ee    ll      9     13
5     1    ff    mm     20     19
6     2    gg    nn              

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