![]() ![]() NA and missing data handling # na_values scalar, str, list-like, or dict, default NoneĪdditional strings to recognize as NA/NaN. Option can improve performance because there is no longer any I/O overhead. If a filepath is provided for filepath_or_buffer, map the file objectĭirectly onto memory and access the data directly from there. (Only valid with C parser) memory_map boolean, default False Use the chunksize or iterator parameter to return the data in chunks. Note that the entire file is read into a single DataFrame regardless, Types either set False, or specify the type with the dtype parameter. While parsing, but possibly mixed type inference. Internally process the file in chunks, resulting in lower memory use Useful for reading pieces of large files. Number of lines at bottom of file to skip (unsupported with engine=’c’). read_csv ( StringIO ( data ), skiprows = lambda x : x % 2 != 0 ) Out: col1 col2 col3 0 a b 2 skipfooter int, default 0 read_csv ( StringIO ( data )) Out: col1 col2 col3 0 a b 1 1 a b 2 2 c d 3 In : pd. Returning names where the callable function evaluates to True: If callable, the callable function will be evaluated against the column names, Instantiate a DataFrame from data with element order preserved use Įlement order is ignored, so usecols= is the same as. ![]() Header row(s) are not taken into account. Inferred from the document header row(s). That correspond to column names provided either by the user in names or integer indices into the document columns) or strings If list-like, all elements must eitherīe positional (i.e. usecols list-like or callable, default None Taken as is and the trailing data are ignored. Than the first row, they are filled with NaN. If the subsequent rows contain less columns The first row after the header is used to determine the number of columns, The body are equal to the number of fields in the header. The first columns are used as index so that the remaining number of fields in Of the data file, then a default index is used. If the number ofįields in the column header row is equal to the number of fields in the body The default value of None instructs pandas to guess. when you have a malformed file with delimiters at Index_col=False can be used to force pandas to not use the firstĬolumn as the index, e.g. index_col int, str, sequence of int / str, or False, optional, default NoneĬolumn(s) to use as the row labels of the DataFrame, either given as If file contains no header row, then you shouldĮxplicitly pass header=None. Line of data rather than the first line of the file. Lines if skip_blank_lines=True, so header=0 denotes the first Note that this parameter ignores commented lines and empty That are not specified will be skipped (e.g. The header can be a list of ints that specify row locationsįor a MultiIndex on the columns e.g. Explicitly pass header=0 to be able to replace Passed explicitly then the behavior is identical to Passed the behavior is identical to header=0 and column namesĪre inferred from the first line of the file, if column names are Default behavior is to infer the column names: if no names are Row number(s) to use as the column names, and the start of theĭata. Column and index locations and names # header int or list of ints, default 'infer' If this option is set to True, nothing should be passed in for theĭelimiter parameter. Specifies whether or not whitespace (e.g. delimiter str, default NoneĪlternative argument name for sep. Note that regexĭelimiters are prone to ignoring quoted data. Will also force the use of the Python parsing engine. In addition, separators longer than 1 character andĭifferent from '\s ' will be interpreted as regular expressions and Used and automatically detect the separator by Python’s builtin sniffer tool,Ĭsv.Sniffer. The separator, but the Python parsing engine can, meaning the latter will be If sep is None, the C engine cannot automatically detect sep str, defaults to ',' for read_csv(), \t for read_table()ĭelimiter to use. Locations), or any object with a read() method (such as an open file or Or py:py._), URL (including http, ftp, and S3 Read_csv() accepts the following common arguments: Basic # filepath_or_buffer variousĮither a path to a file (a str, pathlib.Path, See the cookbook for some advanced strategies. ![]() The workhorse function for reading text files (a.k.a. With from io import StringIO for Python 3. Here is an informal performance comparison for some of these IO methods.įor examples that use the StringIO class, make sure you import it Below is a table containing available readers and ![]() Writer functions are object methods that are accessed likeĭataFrame.to_csv(). Pandas.read_csv() that generally return a pandas object. The pandas I/O API is a set of top level reader functions accessed like ![]()
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