Display rows with one or more NaN values in pandas dataframe

Question

I have a dataframe in which some rows contain missing values    In  31   df head   Out 31                                 alpha1  alpha2    gamma1    gamma2       chi2min   filename                                                                         M66 MI NSRh35d32kpoints dat  0 8016  0 9283  1 000000  0 074804  3 985599e 01    F71 sMI DMRI51d dat          0 0000  0 0000       NaN  0 000000  1 000000e 25    F62 sMI St22d7 dat           1 7210  3 8330  0 237480  0 150000  1 091832e 01    F41 Car HOC498d dat          1 1670  2 8090  0 364190  0 300000  7 966335e 00    F78 MI 547d dat              1 8970  5 4590  0 095319  0 100000  2 593468e 01    I want to display those rows on the screen  If I try df isnull    it gives a long dataframe with True and False  Is there any way by which I can select these rows and print them on the screen

User · Answer

Use df df isnull   any axis 1   for python 3 6 or above

User · Answer

Suppose gamma1 and gamma2 are two such columns for which df isnull   any   gives True value   the following code can be used to print the rows   bool1   pd isnull df  gamma1    bool2   pd isnull df  gamma2    df bool1  df bool2

User · Answer

Can try this too  almost similar previous answers      d     filename     M66 MI NSRh35d32kpoints dat    F71 sMI DMRI51d dat    F62 sMI St22d7 dat    F41 Car HOC498d dat    F78 MI 547d dat     alpha1    0 8016  0 0  1 721  1 167  1 897    alpha2    0 9283  0 0  3 833  2 809  5 459    gamma1    1 0  np nan  0 23748000000000002  0 36419  0 095319    gamma2    0 074804  0 0  0 15  0 3  np nan    chi2min    39 855990000000006  1e 25  10 91832  7 966335000000001  25 93468       df   pd DataFrame d  set index  filename     Count of null values in each column  df isnull   sum     df isnull   any axis 1

User · Answer

You can use DataFrame any with parameter axis 1 for check at least one True in row by DataFrame isna with boolean indexing   df1   df df isna   any axis 1       d     filename     M66 MI NSRh35d32kpoints dat    F71 sMI DMRI51d dat    F62 sMI St22d7 dat    F41 Car HOC498d dat    F78 MI 547d dat     alpha1    0 8016  0 0  1 721  1 167  1 897    alpha2    0 9283  0 0  3 833  2 809  5 459    gamma1    1 0  np nan  0 23748000000000002  0 36419  0 095319    gamma2    0 074804  0 0  0 15  0 3  np nan    chi2min    39 855990000000006  1e 25  10 91832  7 966335000000001  25 93468   df   pd DataFrame d  set index  filename       print  df                               alpha1  alpha2    gamma1    gamma2       chi2min filename                                                                      M66 MI NSRh35d32kpoints dat  0 8016  0 9283  1 000000  0 074804  3 985599e 01 F71 sMI DMRI51d dat          0 0000  0 0000       NaN  0 000000  1 000000e 25 F62 sMI St22d7 dat           1 7210  3 8330  0 237480  0 150000  1 091832e 01 F41 Car HOC498d dat          1 1670  2 8090  0 364190  0 300000  7 966335e 00 F78 MI 547d dat              1 8970  5 4590  0 095319       NaN  2 593468e 01   Explanation   print  df isna                                alpha1 alpha2 gamma1 gamma2 chi2min filename                                                        M66 MI NSRh35d32kpoints dat  False  False  False  False   False F71 sMI DMRI51d dat          False  False   True  False   False F62 sMI St22d7 dat           False  False  False  False   False F41 Car HOC498d dat          False  False  False  False   False F78 MI 547d dat              False  False  False   True   False  print  df isna   any axis 1   filename M66 MI NSRh35d32kpoints dat    False F71 sMI DMRI51d dat             True F62 sMI St22d7 dat             False F41 Car HOC498d dat            False F78 MI 547d dat                 True dtype  bool  df1   df df isna   any axis 1   print  df1                       alpha1  alpha2    gamma1  gamma2       chi2min filename                                                            F71 sMI DMRI51d dat   0 000   0 000       NaN     0 0  1 000000e 25 F78 MI 547d dat       1 897   5 459  0 095319     NaN  2 593468e 01

[python] Display rows with one or more NaN values in pandas dataframe

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