怎么在pandas中使用read_table读取csv文件?相信很多没有经验的人对此束手无策,为此本文总结了问题出现的原因和解决方法,通过这篇文章希望你能解决这个问题。
创新互联公司是一家集做网站、网站建设、网站页面设计、网站优化SEO优化为一体的专业的建站公司,已为成都等多地近百家企业提供网站建设服务。追求良好的浏览体验,以探求精品塑造与理念升华,设计最适合用户的网站页面。 合作只是第一步,服务才是根本,我们始终坚持讲诚信,负责任的原则,为您进行细心、贴心、认真的服务,与众多客户在蓬勃发展的市场环境中,互促共生。查看csv文件的内容如下;
In [10]: cat data.csv index,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.DataFrame
In [13]: data1 Out[13]: index name comment Unnamed: 3 Unnamed: 4 Unnamed: 5 Unnamed: 6 0 1 name_01 coment_01 NaN NaN NaN NaN 1 2 name_02 coment_02 NaN NaN NaN NaN 2 3 name_03 coment_03 NaN NaN NaN NaN 3 4 name_04 coment_04 NaN NaN NaN NaN 4 5 name_05 coment_05 NaN NaN NaN NaN 5 6 name_06 coment_06 NaN NaN NaN NaN 6 7 name_07 coment_07 NaN NaN NaN NaN 7 8 name_08 coment_08 NaN NaN NaN NaN 8 9 name_09 coment_09 NaN NaN NaN NaN 9 10 name_10 coment_10 NaN NaN NaN NaN 10 11 name_11 coment_11 NaN NaN NaN NaN 11 12 name_12 coment_12 NaN NaN NaN NaN 12 13 name_13 coment_13 NaN NaN NaN NaN 13 14 name_14 coment_14 NaN NaN NaN NaN 14 15 name_15 coment_15 NaN NaN NaN NaN 15 16 name_16 coment_16 NaN NaN NaN NaN 16 17 name_17 coment_17 NaN NaN NaN NaN 17 18 name_18 coment_18 NaN NaN NaN NaN 18 19 name_19 coment_19 NaN NaN NaN NaN 19 20 name_20 coment_20 NaN NaN NaN NaN 20 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]: data2 Out[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,,,,
看完上述内容,你们掌握怎么在pandas中使用read_table读取csv文件的方法了吗?如果还想学到更多技能或想了解更多相关内容,欢迎关注创新互联行业资讯频道,感谢各位的阅读!
售后响应及时
7×24小时客服热线数据备份
更安全、更高效、更稳定价格公道精准
项目经理精准报价不弄虚作假合作无风险
重合同讲信誉,无效全额退款