pandas read_csv fails mixed dtypes

Question

I have a csv file which is 63 MB and blood tests of patients. I can't get a DataFrame. It says:

DtypeWarning: Columns (5,12,20,21,22,23,24,25,26,30,32,35,36,37,38,39,40,41,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,121,123,167,169,171,173,175,181,183,189,191,193,195,207,209,211,213,215,217,219,221,223,225,227,229,231,233,235) have mixed types. Specify dtype option on import or set low_memory=False. hmg1 = pd.read_csv("/home/fatih/İndirilenler/sample1-1.csv")

Don't let Pandas infers the datatype of your column: use `hmg1 = pd.read_csv("/home/fatih/İndirilenler/sample1-1.csv", dtype=str)` — Corralien, Mar 11 '22 at 13:39

score 0 · Answer 1 · answered Mar 11 '22 at 13:49

0

Just force the type of your data :

pd.read_csv(path_to_file, dtype=str)

answered Mar 11 '22 at 13:49

Tomo

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How do you know that OP wants `str` dtype? – Serge Ballesta Mar 11 '22 at 14:28
for me it's the best type to get unknown value, obviusly he can choice another type if he need something else – – Tomo Mar 11 '22 at 15:40

pandas read_csv fails mixed dtypes

1 Answers1