read_csv是pandas中专门用于csv文件读取的功能，不过这并不是唯一的处理方式。pandas中还有读取表格的通用函数read_table。

接下来使用read_table功能作一下csv文件的读取尝试，使用此功能的时候需要指定文件中的内容分隔符。

查看csv文件的内容如下；

In [10]: cat data.csvindex,name,comment,,,,1,name_01,coment_01,,,,2,name_02,coment_02,,,,3,name_03,coment_03,,,,4,name_04,coment_04,,,,5,name_05,coment_05,,,,6,name_06,coment_06,,,,7,name_07,coment_07,,,,8,name_08,coment_08,,,,9,name_09,coment_09,,,,10,name_10,coment_10,,,,11,name_11,coment_11,,,,12,name_12,coment_12,,,,13,name_13,coment_13,,,,14,name_14,coment_14,,,,15,name_15,coment_15,,,,16,name_16,coment_16,,,,17,name_17,coment_17,,,,18,name_18,coment_18,,,,19,name_19,coment_19,,,,20,name_20,coment_20,,,,21,name_21,coment_21,,,,

使用pandas读取文件内容如下：In [11]: data1 = pd.read_table('data.csv',sep=',')

In [12]: type(data1)Out[12]: pandas.core.frame.DataFrameIn [13]: data1Out[13]: index name comment Unnamed: 3 Unnamed: 4 Unnamed: 5 Unnamed: 60 1 name_01 coment_01 NaN NaN NaN NaN1 2 name_02 coment_02 NaN NaN NaN NaN2 3 name_03 coment_03 NaN NaN NaN NaN3 4 name_04 coment_04 NaN NaN NaN NaN4 5 name_05 coment_05 NaN NaN NaN NaN5 6 name_06 coment_06 NaN NaN NaN NaN6 7 name_07 coment_07 NaN NaN NaN NaN7 8 name_08 coment_08 NaN NaN NaN NaN8 9 name_09 coment_09 NaN NaN NaN NaN9 10 name_10 coment_10 NaN NaN NaN NaN10 11 name_11 coment_11 NaN NaN NaN NaN11 12 name_12 coment_12 NaN NaN NaN NaN12 13 name_13 coment_13 NaN NaN NaN NaN13 14 name_14 coment_14 NaN NaN NaN NaN14 15 name_15 coment_15 NaN NaN NaN NaN15 16 name_16 coment_16 NaN NaN NaN NaN16 17 name_17 coment_17 NaN NaN NaN NaN17 18 name_18 coment_18 NaN NaN NaN NaN18 19 name_19 coment_19 NaN NaN NaN NaN19 20 name_20 coment_20 NaN NaN NaN NaN20 21 name_21 coment_21 NaN NaN NaN NaN

不过在几番尝试下来，发现这个分隔符缺省的时候倒是也能够读出数据。

In [16]: data2 = pd.read_table('data.csv')In [17]: data2Out[17]: index,name,comment,,,,0 1,name_01,coment_01,,,,1 2,name_02,coment_02,,,,2 3,name_03,coment_03,,,,3 4,name_04,coment_04,,,,4 5,name_05,coment_05,,,,5 6,name_06,coment_06,,,,6 7,name_07,coment_07,,,,7 8,name_08,coment_08,,,,8 9,name_09,coment_09,,,,9 10,name_10,coment_10,,,,10 11,name_11,coment_11,,,,11 12,name_12,coment_12,,,,12 13,name_13,coment_13,,,,13 14,name_14,coment_14,,,,14 15,name_15,coment_15,,,,15 16,name_16,coment_16,,,,16 17,name_17,coment_17,,,,17 18,name_18,coment_18,,,,18 19,name_19,coment_19,,,,19 20,name_20,coment_20,,,,20 21,name_21,coment_21,,,,

不知道此功能对其他格式的数据的读取功能会不会有自动识别的功能，需要继续确认。

以上这篇使用pandas read_table读取csv文件的方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。