loop over dataframe column python

Question

I have three dataframes:

df1, df2, df3.

Each of these dataframes has a variable (column1, column2, column3, respectfully) that has an id with it.

I have a master dataframe, called master_df, with column_master. This column, also, has an ID with it.

I would like to write a loop so that if column_master has any of the ids from df1, df2, or df3, create a new column called 'flag' and flag it: flag1 if the id was found in df1, flag2 if found in df2, flag3 if found in df3.

I attempted this so far, but I am at a loss as to how to finish the code:

def create_flag(df):

if df['column_master'] in df1['column1']:
    return df['flag']==flag_1  
elif df['column_master'] in ('column2'):
    return df['flag']==flag_2   
elif df['column_master'] in ('column3'):
    return df['flag']==flag_3 

    return df 

create_flag(master_df)

This throws off an error saying it does not recognize my column names. What am I doing wrong? and is there a better way to write this?

jpp · Accepted Answer · 2018-11-04 12:46:42Z

2

Avoid row-wise calculations with Pandas. You can use np.select with multiple conditions / values.

dfs = {1: df1, 2: df2, 3: df3}

conds = [df['column_master'].isin(dfx[f'column{idx}']) for idx, dfx in dfs.items()]
choices = [f'flag{i}' for i in range(1, len(conds)+1)]

df['flag'] = np.select(conds, choices, default='flag-None')

edited Nov 4, 2018 at 12:46

answered Nov 4, 2018 at 12:30

jpp

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Comments

Shadab Ahmed · Accepted Answer · 2018-11-04 12:55:28Z

0

In your code, I can see that for else condition you are missing the dataframe names

def create_flag(df):

if df['column_master'] in df1['column1']:
    return df['flag']==flag_1  
elif df['column_master'] in df2['column2']:
    return df['flag']==flag_2   
elif df['column_master'] in df3['column3']:
    return df['flag']==flag_3 

    return df 

create_flag(master_df)

answered Nov 4, 2018 at 12:55

Shadab Ahmed

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