pandas读取数据之read_table()

1. pandas read_table

pandas中读取表格的通用函数：read_table
read_table()读取以‘/t’分割的文件到DataFrame
read_table如何读取csv文件？

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2.在缺省分隔符的时候，依然可以读出数据:

(摘自：https://www.jb51.net/article/143164.htm)

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3. pandas中read_table的参数

              pandas.read_table(filepath_or_buffer,sep='\t',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)

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4.如果文本中的分割符既有空格又有制表符（‘/t’），sep参数用‘/s+’，可以匹配任何空格。 代码如下：

import pandas as pd
df_txt = pd.read_csv('BSEP_NMC_ATME_SOB_EAQI_ACHN_LNO_P9_20160101060000000.TXT',sep='\s+')
print df_txt

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5.为行和列添加索引

用参数names添加列索引，用index_col添加行索引

import pandas as pd
df_txt = pd.read_csv('BSEP_NMC_ATME_SOB_EAQI_ACHN_LNO_P9_20160101060000000.TXT',sep='\s+',
                 names=['1','2','3','4','5','6','7','8','9','10','11'],index_col=0,header=1)
print df_txt

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6.去掉diamond那一行，用header来操作

import pandas as pd
df_txt = pd.read_csv('BSEP_NMC_ATME_SOB_EAQI_ACHN_LNO_P9_20160101060000000.TXT',sep='\s+',
                 names=['1','2','3','4','5','6','7','8','9','10','11'],index_col=0,header=1)
 print df_txt

（摘自:https://blog.csdn.net/shener_m/article/details/81047669）