在 python pandas 中读取缺失值的文件 [英] reading file with missing values in python pandas

问题描述

我尝试使用 pandas.read_csv 读取缺少值的 .txt.我的数据格式为:

I try to read .txt with missing values using pandas.read_csv. My data is of the format:

10/08/2012,12:10:10,name1,0.81,4.02,50;18.5701400N,4;07.7693770E,7.92,10.50,0.0106,4.30,0.0301
10/08/2012,12:10:11,name2,,,,,10.87,1.40,0.0099,9.70,0.0686

具有数千个具有相同点名称、gps 位置和其他读数的样本.我使用代码:

with thousands of samples with same name of the point, gps position, and other readings. I use a code:

myData = read_csv('~/data.txt', sep=',', na_values='')

代码错误，因为 na_values 没有给出 NaN 或其他指标.列应该具有相同的大小，但我以不同的长度完成.

The code is wrong as na_values does not gives NaN or other indicator. Columns should have the same size but I finish with different length.

我不知道在 na_values 之后到底应该输入什么(尝试了所有不同的东西).谢谢

I don't know what exactly should be typed in after na_values (did try all different things). Thanks

推荐答案

参数 na_values 必须是list like"(参见这个 答案).

The parameter na_values must be "list like" (see this answer).

一个字符串是类似列表"，所以:

A string is "list like" so:

na_values='abc' # would transform the letters 'a', 'b' and 'c' each into `nan`
# is equivalent to
na_values=['a','b','c']

同样:

na_values=''
# is equivalent to
na_values=[] # and this is not what you want!

这意味着您需要使用na_values=[''].

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