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pandas ¼¿ isna isnull notna notnull
# 45 JMJS    24.1.28 15:35

import pandas as pd
import numpy  as np

col  = [ 'col1','col2', 'col3' ,'col4']
row  = [ 'row1','row2', 'row3' ]
data = [[    1 ,    2 ,  pd.NA ,    4 ],
        [np.nan,    6 , np.inf ,    8 ],
        [    9 ,  ' ' ,     '' , None ]]

df = pd.DataFrame(data,row,col)

print(df,'\n')
#      col1  col2  col3  col4
#row1   1.0     2  <NA>   4.0
#row2   NaN     6   inf   8.0
#row3   9.0               NaN

print(' isna',df.isnull(),'\n')  #  isna ==  isnull
# isna  col1   col2   col3   col4
#row1  False  False   True  False
#row2   True  False  False  False
#row3  False  False  False   True

print('notna',df.notna() ,'\n')  # notna == notnull
#notna  col1  col2   col3   col4
#row1   True  True  False   True
#row2  False  True   True   True
#row3   True  True   True  False

df.at['row4','col5']=45
df.at['row5','col7']=57
print(df,'\n')
#      col1 col2  col3  col4  col5  col7
#row1   1.0    2  <NA>   4.0   NaN   NaN
#row2   NaN    6   inf   8.0   NaN   NaN
#row3   9.0              NaN   NaN   NaN
#row4   NaN  NaN   NaN   NaN  45.0   NaN
#row5   NaN  NaN   NaN   NaN   NaN  57.0

print('  index:',df.index,'\n')
#  index: Index(['row1', 'row2', 'row3', 'row4', 'row5'], dtype='object')

print('columns:',df.columns,'\n')
#columns: Index(['col1', 'col2', 'col3', 'col4', 'col5', 'col7'], dtype='object')

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