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Exception that is raised by an error encountered in parsing file contents.
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See Also
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read_csv : Read CSV (comma-separated) file into a DataFrame.
read_html : Read HTML table into a DataFrame.
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Warning raised when reading different dtypes in a column from a file.
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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.
>>> import os
>>> os.remove('test.csv')
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Warning raised when reading a file that doesn't use the default 'c' parser.
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It happens due to a lack of support or functionality for parsing a
particular attribute of a CSV file with the requested engine.
Currently, 'c' unsupported options include the following parameters:
1. `sep` other than a single character (e.g. regex separators)
2. `skipfooter` higher than 0
3. `sep=None` with `delim_whitespace=False`
The warning can be avoided by adding `engine='python'` as a parameter in
`pd.read_csv` and `pd.read_table` methods.
See Also
--------
pd.read_csv : Read CSV (comma-separated) file into DataFrame.
pd.read_table : Read general delimited file into DataFrame.
Examples
--------
Using a `sep` in `pd.read_csv` other than a single character:
>>> import io
>>> csv = '''a;b;c
... 1;1,8
... 1;2,1'''
>>> df = pd.read_csv(io.StringIO(csv), sep='[;,]') # doctest: +SKIP
... # ParserWarning: Falling back to the 'python' engine...
Adding `engine='python'` to `pd.read_csv` removes the Warning:
>>> df = pd.read_csv(io.StringIO(csv), sep='[;,]', engine='python')
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.. versionadded:: 1.1.0
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