Import pandas dataframe column as string not int

Question

I would like to import the following csv as strings not as int64  Pandas read csv automatically converts it to int64  but I need this column as string   ID 00013007854817840016671868 00013007854817840016749251 00013007854817840016754630 00013007854817840016781876 00013007854817840017028824 00013007854817840017963235 00013007854817840018860166   df   read csv  sample csv    df ID  gt  gt   0   -9223372036854775808 1   -9223372036854775808 2   -9223372036854775808 3   -9223372036854775808 4   -9223372036854775808 5   -9223372036854775808 6   -9223372036854775808 Name  ID   Unfortunately using converters gives the same result    df   read csv  sample csv   converters   ID   str   df ID  gt  gt   0   -9223372036854775808 1   -9223372036854775808 2   -9223372036854775808 3   -9223372036854775808 4   -9223372036854775808 5   -9223372036854775808 6   -9223372036854775808 Name  ID

User · Answer

This probably isn t the most elegant way to do it  but it gets the job done   In 1   import numpy as np  In 2   import pandas as pd  In 3   df   pd DataFrame np genfromtxt   Users spencerlyon2 Desktop test csv   dtype str  1    columns   ID     In 4   df Out 4                           ID 0  00013007854817840016671868 1  00013007854817840016749251 2  00013007854817840016754630 3  00013007854817840016781876 4  00013007854817840017028824 5  00013007854817840017963235 6  00013007854817840018860166   Just replace   Users spencerlyon2 Desktop test csv  with the path to your file

User · Answer

Just want to reiterate this will work in pandas  gt   0 9 1  In  2   read csv  sample csv   dtype   ID   object   Out 2                               ID 0  00013007854817840016671868 1  00013007854817840016749251 2  00013007854817840016754630 3  00013007854817840016781876 4  00013007854817840017028824 5  00013007854817840017963235 6  00013007854817840018860166  I m creating an issue about detecting integer overflows also  EDIT  See resolution here  https   github com pydata pandas issues 2247 Update as it helps others  To have all columns as str  one can do this  from the comment   pd read csv  sample csv   dtype   str   To have most or selective columns as str  one can do this    lst of column names which needs to be string lst str cols     prefix    serial     use dictionary comprehension to make dict of dtypes dict dtypes    x    str   for x in lst str cols    use dict on dtypes pd read csv  sample csv   dtype dict dtypes

User · Answer

Since pandas 1 0 it became much more straightforward  This will read column  ID  as dtype  string         pd read csv  sample csv  dtype   ID   string      As we can see in this Getting started guide   string  dtype has been introduced  before strings were treated as dtype  object

[python] Import pandas dataframe column as string not int

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