How To Create A Dict/object/mapping In An Aggregation Field
I have the following groupedby object in pandas: df_grouped = df.groupby(by=['resolution','media_type', 'asset_type']).file_name print (type(df_grouped)) #
Solution 1:
You can first omit file_name after groupby, because need processing also md5 column. Then use lambda function for convert columns to dictionaries per groups, output is Series:
df_grouped = df.groupby(by=['resolution','media_type', 'asset_type'])
series = df_grouped.apply(lambda x: dict(zip(x['file_name'],x['md5'])))
Or:
series = df_grouped.apply(lambda x: dict(x[['file_name','md5']].to_numpy()))
Sample:
print (df)
resolution media_type asset_type file_name md5
0 HD Video Feature LG_ALPHAASP_EN__L102 1
1 HD Video Promo Alphap_2ch.mov 2
2 HD Video Trailer LG_ALPHAX9 3
3 HD Video Trailer LG_ALPHAX9_178_2 4
df_grouped = df.groupby(by=['resolution','media_type', 'asset_type'])
series = df_grouped.apply(lambda x: dict(x[['file_name','md5']].to_numpy()))
print (series)
resolution media_type asset_type
HD Video Feature {'LG_ALPHAASP_EN__L102': 1}
Promo {'Alphap_2ch.mov': 2}
Trailer {'LG_ALPHAX9': 3, 'LG_ALPHAX9_178_2': 4}
dtype: object
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