What is dtype O in pandas

Question

I have a dataframe in pandas and I m trying to figure out what the types of its values are  I am unsure what the type is of column  Test   However  when I run myFrame  Test   dtype  I get   dtype  O     What does this mean

User · Answer

It means  a python object   i e  not one of the builtin scalar types supported by numpy   np array  object     dtype   gt  dtype  O

User · Answer

O  stands for object    Loading a csv file as a dataframe import pandas as pd  train df   pd read csv  train csv   col name    Name of Employee    Checking the datatype of column name train df col name  dtype   Instead try printing the same thing print train df col name  dtype   The first line returns  dtype  O    The line with the print statement returns the following  object

User · Answer

It means    O       Python  objects   Source      The first character specifies the kind of data and the remaining characters specify the number of bytes per item  except for Unicode  where it is interpreted as the number of characters  The item size must correspond to an existing type  or an error will be raised  The supported kinds are   to an existing type  or an error will be raised  The supported kinds are     b        boolean  i         signed  integer  u        unsigned integer  f        floating-point  c        complex-floating point  O         Python  objects  S    a    byte- string  U        Unicode  V        raw data  void    Another answer helps if need check types

User · Answer

When you see dtype  O   inside dataframe this means Pandas string   What is dtype   Something that belongs to pandas or numpy  or both  or something else  If we examine pandas code   df   pd DataFrame   float    1 0                        int    1                        datetime    pd Timestamp  20180310                          string     foo     print df  print df  float   dtype df  int   dtype df  datetime   dtype df  string   dtype  df  string   dtype   It will output like this      float  int   datetime string     0    1 0    1 2018-03-10    foo --- float64 int64 datetime64 ns  object --- dtype  O     You can interpret the last as Pandas dtype  O   or Pandas object which is Python type string  and this corresponds to Numpy string   or unicode  types   Pandas dtype    Python type     NumPy type          Usage object          str             string   unicode    Text   Like Don Quixote is on ass  Pandas is on Numpy and Numpy understand the underlying  architecture of your system and uses the class numpy dtype for that   Data type object is an instance of numpy dtype class that understand the data type more precise including    Type of the data  integer  float  Python object  etc   Size of the data  how many bytes is in e g  the integer  Byte order of the data  little-endian or big-endian  If the data type is structured  an aggregate of other data types   e g   describing an array item consisting of an integer and a float  What are the names of the  fields  of the structure What is the data-type of each field  Which part of the memory block each field takes If the data type is a sub-array  what is its shape and data type     In the context of this question dtype belongs to both pands and numpy and in particular dtype  O   means we expect the string     Here is some code for testing with explanation  If we have the dataset as dictionary  import pandas as pd import numpy as np from pandas import Timestamp  data   id    0  1  1  2  2  3  3  4  4  5    date    0  Timestamp  2018-12-12 00 00 00    1  Timestamp  2018-12-12 00 00 00    2  Timestamp  2018-12-12 00 00 00    3  Timestamp  2018-12-12 00 00 00    4  Timestamp  2018-12-12 00 00 00      role    0   Support   1   Marketing   2   Business Development   3   Sales   4   Engineering     num    0  123  1  234  2  345  3  456  4  567    fnum    0  3 14  1  2 14  2  -0 14  3  41 3  4  3 14   df   pd DataFrame from dict data   now we have a dataframe  print df  print df dtypes    The last lines will examine the dataframe and note the output      id       date                  role  num   fnum 0   1 2018-12-12               Support  123   3 14 1   2 2018-12-12             Marketing  234   2 14 2   3 2018-12-12  Business Development  345  -0 14 3   4 2018-12-12                 Sales  456  41 30 4   5 2018-12-12           Engineering  567   3 14 id               int64 date    datetime64 ns  role            object num              int64 fnum           float64 dtype  object   All kind of different dtypes  df iloc 1      np nan df iloc 2      None   But if we try to set np nan or None this will not affect the original column dtype  The output will be like this   print df  print df dtypes       id       date         role    num   fnum 0  1 0 2018-12-12      Support  123 0   3 14 1  NaN        NaT          NaN    NaN    NaN 2  NaN        NaT         None    NaN    NaN 3  4 0 2018-12-12        Sales  456 0  41 30 4  5 0 2018-12-12  Engineering  567 0   3 14 id             float64 date    datetime64 ns  role            object num            float64 fnum           float64 dtype  object   So np nan or None will not change the columns dtype  unless we set the all column rows to np nan or None  In that case column will become float64 or object respectively   You may try also setting single rows   df iloc 3      0   will convert datetime to object only df iloc 4           will convert all columns to object   And to note here  if we set string inside a non string column it will become string or object dtype

[python] What is dtype('O'), in pandas?

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