pandas : Lambda ,Map and Eval Conditions

Lambda ,Map and eval in Pandas

1. Simple 

import pandas as pd

a=pd.DataFrame({"a":["deea","123","deep","deepak"]})

b=pd.DataFrame({"b":["deeap","1234","deepak","deepa"]})

c=pd.DataFrame(map(lambda x,y:x in y,a['a'],b['b']))

print(c)

 

 

result : 

       0

0   True

1   True

2   True

3  False 

 

2. Using Dynamic Formula :

import pandas as pd

a=pd.DataFrame({"a":["deea","123","deep","deepak"]})

b=pd.DataFrame({"b":["deeap","1234","deepak","deepa"]})

c=pd.DataFrame(map(eval(input("enter -lambda x,y:x in y")),a['a'].values,b['b'].values))

print(c)

       0

0   True

1   True

2   True

3  False

 

3)Using Dynamic Formula and 1st columns

import pandas as pd

a=pd.DataFrame({"a":["deea","123","deep","deepak"]})

b=pd.DataFrame({"b":["deeap","1234","deepak","deepa"]})

c=pd.DataFrame(map(eval(input("enter -lambda x,y:x in y")),a.iloc[:,0],b.iloc[:,0]))

print(c)

  

Result: 

  0

0 True

1 True

2 True

3 False 

 

"""

"""

Column Names

data.iloc[:,0] # first column of data frame (first_name)
data.iloc[:,1] # second column of data frame (last_name)
data.iloc[:,-1] # last column of data frame (id)

Rows and Columns
data.iloc[0:5] # first five rows of dataframe
data.iloc[:, 0:2] # first two columns of data frame with all rows
data.iloc[[0,3,6,24], [0,5,6]] # 1st, 4th, 7th, 25th row + 1st 6th 7th columns.
data.iloc[0:5, 5:8] # first 5 rows and 5th, 6th, 7th columns of data frame
"""