How to convert datatype object to float64 in python

Question

I am going around in circles and tried so many different ways so I guess my core understanding is wrong  I would be grateful for help in understanding my encoding decoding issues   I import the dataframe from SQL and it seems that some datatypes float64 are converted to Object  Thus  I cannot do any calculation  I fail to convert the Object back to float64   df head    Date        WD  Manpower 2nd     CTR    2ndU    T1    T2      T3      T4   2013 4 6    6   NaN     2 645   5 27    0 29    407     533     454     368 2013 4 7    7   NaN     2 118   5 89    0 31    257     659     583     369 2013 4 13   6   NaN     2 470   5 38    0 29    354     531     473   383 2013 4 14   7   NaN     2 033   6 77    0 37    396     748     681     458 2013 4 20   6   NaN     2 690   5 38    0 29    361     528     541     381   df dtypes  WD             float64 Manpower       float64 2nd             object CTR             object 2ndU           float64 T1              object T2              object T3              object T4              object T5              object  dtype  object   SQL table

User · Answer

convert objects is deprecated   For pandas    0 17 0  use pd to numeric  df  2nd     pd to numeric df  2nd

User · Answer

X   np array X  dtype float   You can use this to convert to array of float in python 3 7 6

User · Answer

You can try this    df  2nd     pd to numeric df  2nd   str replace           df  CTR     pd to numeric df  CTR   str replace

User · Answer

Or you can use regular expression to handle multiple items as the general case of this issue     df  2nd     pd to numeric df  2nd   str replace r              df  CTR     pd to numeric df  CTR   str replace r    d

User · Answer

I had this problem in a DataFrame  df  created from an Excel-sheet with several internal header rows   After cleaning out the internal header rows from df  the columns  values were of  non-null object  type  DataFrame info      This code converted all numerical values of multiple columns to int64 and float64 in one go   for i in range 0  len df columns        df iloc   i    pd to numeric df iloc   i   errors  ignore         errors  ignore  lets strings remain as  non-null objects

User · Answer

You can convert most of the columns by just calling convert objects   In  36    df   df convert objects convert numeric True  df dtypes Out 36   Date         object WD            int64 Manpower    float64 2nd          object CTR          object 2ndU        float64 T1            int64 T2          int64 T3           int64 T4        float64 dtype  object   For column  2nd  and  CTR  we can call the vectorised str methods to replace the thousands separator and remove the     sign and then astype to convert   In  39    df  2nd     df  2nd   str replace         astype int  df  CTR     df  CTR   str replace         astype np float64  df dtypes Out 39   Date         object WD            int64 Manpower    float64 2nd           int32 CTR         float64 2ndU        float64 T1            int64 T2            int64 T3            int64 T4           object dtype  object In  40    df head   Out 40           Date  WD  Manpower   2nd   CTR  2ndU   T1    T2   T3     T4 0   2013 4 6   6       NaN  2645  5 27  0 29  407   533  454    368 1   2013 4 7   7       NaN  2118  5 89  0 31  257   659  583    369 2  2013 4 13   6       NaN  2470  5 38  0 29  354   531  473    383 3  2013 4 14   7       NaN  2033  6 77  0 37  396   748  681    458 4  2013 4 20   6       NaN  2690  5 38  0 29  361   528  541    381   Or you can do the string handling operations above without the call to astype and then call convert objects to convert everything in one go   UPDATE  Since version 0 17 0 convert objects is deprecated and there isn t a top-level function to do this so you need to do   df apply lambda col pd to numeric col  errors  coerce     See the docs and this related question  pandas  to numeric for multiple columns

[python] How to convert datatype:object to float64 in python?

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