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Poster has an example which tricks read_csv into thinking column a is a int, but then throws it lots of strings (and it then infers 1s as strings).
import pandas as pd df = pd.DataFrame({'a':['1']*100000 + ['X']*100000 + ['1']*100000, 'b':['b']*300000}) df.to_csv('test', sep='\t', index=False, na_rep='NA') df2 = pd.read_csv('test', sep='\t') print df2['a'].unique()
http://stackoverflow.com/questions/18471859/pandas-read-csv-dtype-inference-issue
I think this is rather an edge case tbh. :)
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He (or someone) beat you to it. #4691
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I did not do a very good search. #4691
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Poster has an example which tricks read_csv into thinking column a is a int, but then throws it lots of strings (and it then infers 1s as strings).
http://stackoverflow.com/questions/18471859/pandas-read-csv-dtype-inference-issue
I think this is rather an edge case tbh. :)
The text was updated successfully, but these errors were encountered: