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multi indexing in pandas dataframe

Ashamed Angelfish answered on November 5, 2023 Popularity 6/10 Helpfulness 2/10

answer multi indexing in pandas dataframe

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multi indexing in pandas dataframe

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#iterate only through rows with missing LoanAmount
for i,row in data.loc[data['LoanAmount'].isnull(),:].iterrows():
  ind = tuple([row['Gender'],row['Married'],row['Self_Employed']])
  data.loc[i,'LoanAmount'] = impute_grps.loc[ind].values[0]

#Now check the #missing values again to confirm:
print data.apply(num_missing, axis=0)

Popularity 6/10 Helpfulness 2/10 Language python

Source: www.analyticsvidhya.com

Tags: dataframe pandas python

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Contributed on Mar 08 2024

Ashamed Angelfish

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pandas multi level index

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df.set_index(['col1', 'col2']) # Set/Create multi-level index
df.loc[[('col1val1','col2val1'), ('col1val2','col2val2')]] # Subsetting using multi-level index

Popularity 8/10 Helpfulness 5/10 Language python

Source: Grepper

Tags: pandas python multi-level m

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Contributed on Nov 05 2023

Innocent Iguana

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multi indexing in pandas dataframe

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