pandas.io.parsers.read_csv¶
- pandas.io.parsers.read_csv(filepath_or_buffer, sep=', ', header=0, index_col=None, names=None, skiprows=None, na_values=None, parse_dates=False, date_parser=None, nrows=None, iterator=False, chunksize=None, skip_footer=0, converters=None, verbose=False, delimiter=None, encoding=None)¶
Read CSV (comma-separated) file into DataFrame
Also supports optionally iterating or breaking of the file into chunks.
Parameters : filepath_or_buffer : string or file handle / StringIO. The string could be
a URL. Valid URL schemes include http://, ftp://, and file://. For file:// URLs, a host is expected. For instance, a local file could be file://localhost/path/to/table.csv
sep : string, default ‘,’
Delimiter to use. If sep is None, will try to automatically determine this
header : int, default 0
Row to use for the column labels of the parsed DataFrame
skiprows : list-like or integer
Row numbers to skip (0-indexed) or number of rows to skip (int)
index_col : int or sequence, default None
Column to use as the row labels of the DataFrame. If a sequence is given, a MultiIndex is used.
names : array-like
List of column names
na_values : list-like or dict, default None
Additional strings to recognize as NA/NaN. If dict passed, specific per-column NA values
parse_dates : boolean, default False
Attempt to parse dates in the index column(s)
date_parser : function
Function to use for converting dates to strings. Defaults to dateutil.parser
nrows : int, default None
Number of rows of file to read. Useful for reading pieces of large files
iterator : boolean, default False
Return TextParser object
chunksize : int, default None
Return TextParser object for iteration
skip_footer : int, default 0
Number of line at bottom of file to skip
converters : dict. optional
Dict of functions for converting values in certain columns. Keys can either be integers or column labels
verbose : boolean, default False
Indicate number of NA values placed in non-numeric columns
delimiter : string, default None
Alternative argument name for sep
encoding : string, default None
Encoding to use for UTF when reading/writing (ex. ‘utf-8’)
Returns : result : DataFrame or TextParser