Replacing Pandas or Numpy Nan with a None to use with MysqlDB

Question

I am trying to write a Pandas dataframe  or can use a numpy array  to a mysql database using MysqlDB   MysqlDB doesn t seem understand  nan  and my database throws out an error saying nan is not in the field list  I need to find a way to convert the  nan  into a NoneType   Any ideas

User · Answer

After stumbling around  this worked for me   df   df astype object  where pd notnull df  None

User · Answer

Quite old  yet I stumbled upon the very same issue  Try doing this   df  col replaced     df  col with npnans   apply lambda x  None if np isnan x  else x

User · Answer

Another addition  be careful when replacing multiples and converting the type of the column back from object to float  If you want to be certain that your None s won t flip back to np NaN s apply  andy-hayden s suggestion with using pd where  Illustration of how replace can still go  wrong    In  1   import pandas as pd  In  2   import numpy as np  In  3   df   pd DataFrame   a    1  np NAN  np inf     In  4   df Out 4        a 0  1 0 1  NaN 2  inf  In  5   df replace  np NAN  None   Out 5         a 0     1 1  None 2   inf  In  6   df replace  np NAN  None  np inf  None   Out 6        a 0  1 0 1  NaN 2  NaN  In  7   df where  pd notnull df    None  replace  np inf  None   Out 7        a 0  1 0 1  NaN 2  NaN

User · Answer

bogatron has it right  you can use where  it s worth noting that you can do this natively in pandas   df1   df where pd notnull df   None    Note  this changes the dtype of all columns to object   Example   In  1   df   pd DataFrame  1  np nan    In  2   df Out 2        0 0   1 1 NaN  In  3   df1   df where pd notnull df   None   In  4   df1 Out 4          0 0     1 1  None     Note  what you cannot do recast the DataFrames dtype to allow all datatypes types  using astype  and then the DataFrame fillna method   df1   df astype object  replace np nan   None     Unfortunately neither this  nor using replace  works with None see this  closed  issue     As an aside  it s worth noting that for most use cases you don t need to replace NaN with None  see this question about the difference between NaN and None in pandas   However  in this specific case it seems you do  at least at the time of this answer

User · Answer

Just an addition to  Andy Hayden s answer   Since DataFrame mask is the opposite twin of DataFrame where  they have the exactly same signature but with opposite meaning    DataFrame where is useful for Replacing values where the condition is False   DataFrame mask is used for Replacing values where the condition is True    So in this question  using df mask df isna    other None  inplace True  might be more intuitive

User · Answer

You can replace nan with None in your numpy array    gt  gt  gt  x   np array  1  np nan  3    gt  gt  gt  y   np where np isnan x   None  x   gt  gt  gt  print y  1 0 None 3 0   gt  gt  gt  print type y 1    lt type  NoneType  gt

User · Answer

df   df replace  np nan  None     Credit goes to this guy here on this Github issue

[python] Replacing Pandas or Numpy Nan with a None to use with MysqlDB

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