[FIXED] Row and Column number of empty value present in dataframe in Python

Issue

I have a data frame - the table below

row_id	name	email	age	state
1	Sta	[email protected]	29	AK
2	NaN	[email protected]	NaN	NB
3	Elle	NaN	32	CA
4	Elle	NaN	44	NaN

I want to have the row id and column name wherever my df is NaN/Empty in the below format

row_id	col_id	value
2	Name	NaN
2	age	NaN
3	name	NaN
4	name	NaN
4	state	NaN

import numpy as np
tmp = pd.DataFrame(columns= ['row_id', 'col_id','Value','Gap'], dtype=object) #Creating new DF

for name, values in proc_df.iteritems():           #For loop by items
    for i,v in enumerate(values.tolist()):    #For loop on values
        if np.isnan(v):
            tmp.loc[len(tmp)] = [proc_df.at[i,'row_id'], name, v, len([v])]

tmp

but I am getting the below error

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

Solution

Here, my basic idea is to read DF by columns and if its founds None value create new list and append into new df the list such as [2, A, NaN, 1].

Note : Dont know your logic for GAP column, so am just counting the None value in that specific cell.

Code:

import pandas as pd
tmp = pd.DataFrame(columns= ['row_id', 'Col_id','Value']) #Creating new DF

for name, values in df.iteritems():           #For loop by items
    for i,v in enumerate(values.tolist()):    #For loop on values
        if pd.isna(v):
            tmp.loc[len(tmp)] = [df.at[i,'row_id'], name, v]

tmp

Output:

    row_id  Col_id  Value
0   2       name    None
1   3       email   None
2   4       email   None
3   2       age     None
4   4       sate    None

Answered By - R. Baraiya