pandas.errors.DtypeWarning#
- exception pandas.errors.DtypeWarning[source]#
Warning raised when reading different dtypes in a column from a file.
Raised for a dtype incompatibility. This can happen whenever read_csv or read_table encounter non-uniform dtypes in a column(s) of a given CSV file.
See also
read_csv
Read CSV (comma-separated) file into a DataFrame.
read_table
Read general delimited file into a DataFrame.
Notes
This warning is issued when dealing with larger files because the dtype checking happens per chunk read.
Despite the warning, the CSV file is read with mixed types in a single column which will be an object type. See the examples below to better understand this issue.
Examples
This example creates and reads a large CSV file with a column that contains int and str.
>>> df = pd.DataFrame({'a': (['1'] * 100000 + ['X'] * 100000 + ... ['1'] * 100000), ... 'b': ['b'] * 300000}) >>> df.to_csv('test.csv', index=False) >>> df2 = pd.read_csv('test.csv') ... # DtypeWarning: Columns (0) have mixed types
Important to notice that
df2
will contain both str and int for the same input, ‘1’.>>> df2.iloc[262140, 0] '1' >>> type(df2.iloc[262140, 0]) <class 'str'> >>> df2.iloc[262150, 0] 1 >>> type(df2.iloc[262150, 0]) <class 'int'>
One way to solve this issue is using the dtype parameter in the read_csv and read_table functions to explicit the conversion:
>>> df2 = pd.read_csv('test.csv', sep=',', dtype={'a': str})
No warning was issued.