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, 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, escapechar=None, comment=None, encoding=None, dialect=None, tupleize_cols=None, error_bad_lines=True, warn_bad_lines=True, skipfooter=0, doublequote=True, delim_whitespace=False, low_memory=True, memory_map=False, float_precision=None)
sep=',' # 以,为数据分隔符
shkiprows= 10 # 跳过前十行
nrows = 10 # 只去前10行
parse_dates = ['col_name'] # 指定某行读取为日期格式
index_col = ['col_1','col_2'] # 读取指定的几列
error_bad_lines = False # 当某行数据有问题时,不报错,直接跳过,处理脏数据时使用
na_values = 'NULL' # 将NULL识别为空值
后续有空把每一个参数都搞清楚
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2019-01-09 23:24:00写于济南