Pandas: Conditionally replace values based on other columns values

Question

I have a dataframe (df) that looks like this:

                    environment     event   
time                    
2017-04-28 13:08:22     NaN         add_rd  
         


        

Answer 1

Now my goal is for each add_rd in the event column, the associated NaN-value in the environment column should be replaced with a string RD.

As per @Zero's comment, use pd.DataFrame.loc and Boolean indexing:

df.loc[df['event'].eq('add_rd') & df['environment'].isnull(), 'environment'] = 'RD'

Answer 2

You could consider using where:

df.environment.where((~df.environment.isnull()) & (df.event != 'add_rd'),
                     'RD', inplace=True)

If the condition is not met, the values is replaced by the second element.

Answer 3

if you want to replace just 'add_rd' with 'RD', this can be useful to you

keys_to_replace = {'add_rd':'RD','add_env':'simple'}
df['environment'] = df.groupby(['event'])['environment'].fillna(keys_to_replace['add_rd'])
df

output:

    environment event
0   RD          add_rd
1   RD          add_rd
2   test        add_env
3   prod        add_env

if you have many values to replace based on event, then you may need to follow groupby with 'event' column values

keys_to_replace = {'add_rd':'RD','add_env':'simple'}
temp = df.groupby(['event']).apply(lambda x:  x['environment'].fillna(keys_to_replace[x['event'].values[0]]))
temp.index = temp.index.droplevel(0)
df['environment'] = temp.sort_index().values

output:

   environment  event
0   RD          add_rd
1   RD          add_rd
2   test        add_env
3   prod        add_env

Answer 4

Here it is:

 df['environment']=df['environment'].fillna('RD')