Given a Dataframe, return all those index labels for which some condition is satisfied over a specific column. Solution #1: We can use simple indexing operation to select all those values in the column which satisfies the given condition.
# importing pandas as pd import pandas as pd
# Create the dataframe df = pd.DataFrame({ 'Date' :[ '10/2/2011' , '11/2/2011' , '12/2/2011' , '13/2/2011' ],
'Product' :[ 'Umbrella' , 'Mattress' , 'Badminton' , 'Shuttle' ],
'Last_Price' :[ 1200 , 1500 , 1600 , 352 ],
'Updated_Price' :[ 1250 , 1450 , 1550 , 400 ],
'Discount' :[ 10 , 10 , 10 , 10 ]})
# Create the indexes df.index = [ 'Item 1' , 'Item 2' , 'Item 3' , 'Item 4' ]
# Print the dataframe print (df)
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Output :
# Select all the rows which satisfies the criteria # convert the collection of index labels to list. Index_label = df[df[ 'Updated Price' ]> 1000 ].index.tolist()
# Print all the labels print (Index_label)
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Output :
# importing pandas as pd import pandas as pd
# Create the dataframe df = pd.DataFrame({ 'Date' :[ '10/2/2011' , '11/2/2011' , '12/2/2011' , '13/2/2011' ],
'Product' :[ 'Umbrella' , 'Mattress' , 'Badminton' , 'Shuttle' ],
'Last_Price' :[ 1200 , 1500 , 1600 , 352 ],
'Updated_Price' :[ 1250 , 1450 , 1550 , 400 ],
'Discount' :[ 10 , 10 , 10 , 10 ]})
# Create the indexes df.index = [ 'Item 1' , 'Item 2' , 'Item 3' , 'Item 4' ]
# Print the dataframe print (df)
|
Output :
# Select all the rows which satisfies the criteria # convert the collection of index labels to list. Index_label = df.query( 'Updated_Price > 1000' ).index.tolist()
# Print all the labels print (Index_label)
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Output :