pandas.read_csv(filepath_or_buffer, sep=', ', delimiter=None, header='infer', names=None, index_col=None, usecols=None, squeeze=False, prefix=None, mangle_dupe_cols=True, dtype=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, skiprows=None, skipfooter=0, nrows=None, na_values=None, keep_default_na=True, na_filter=True, verbose=False, skip_blank_lines=True, parse_dates=False, infer_datetime_format=False, keep_date_col=False, date_parser=None, dayfirst=False, iterator=False, chunksize=None, compression='infer', thousands=None, decimal=b'.', lineterminator=None, quotechar='"', quoting=0, doublequote=True, escapechar=None, comment=None, encoding=None, dialect=None, tupleize_cols=None, error_bad_lines=True, warn_bad_lines=True, delim_whitespace=False, low_memory=True, memory_map=False, float_precision=None)
pd.read_csv('*.csv', sep / delimiter='\t')
pd.read_csv('*.csv', header=0) # take the first row as column names
pd.read_csv('*.csv', header=None, names=['column_name1', ..., 'column_namen']) # use names as column names
pd.read_csv('*.csv', header=0, names=['column_name1', ..., 'column_namen']) # use names to replace the first row as column # names
pd.read_csv('*.csv', index_col=None) # use order as index
pd.read_csv('*.csv', index_col=False) # not use the first column as index
pd.read_csv('*.csv', index_col=0) # use the first column as index
pd.read_csv('*.csv', usecols=[0, 1, ..., q])
pd.read_csv('*.csv', usecols=['column0', 'column1', ..., 'columnq'])
pd.read_csv('*.csv', dtype=DataType) # for all data
pd.read_csv('*.csv', dtype=object) # for example
pd.read_csv('*.csv', dtype={'column1': DataType1, ..., 'columnn': DataTypen})
print(pd.dtypes)
http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html?highlight=read_csv
#%%
df.to_csv('*.csv', index=False) # not save index