python read_fwf错误:"python-fwf解析器不支持dtype" [英] python read_fwf error: 'dtype is not supported with python-fwf parser'

问题描述

使用python 2.7.5和pandas 0.12.0，我试图使用'pd.io.parsers.read_fwf()'将固定宽度字体的文本文件导入到DataFrame中.我要导入的值都是数字，但是保留前导零非常重要，因此我想将dtype指定为字符串而不是int.

Using python 2.7.5 and pandas 0.12.0, I'm trying to import fixed-width-font text files into a DataFrame with 'pd.io.parsers.read_fwf()'. The values I'm importing are all numeric, but it's important that leading zeros be preserved, so I'd like to specify the dtype as string rather than int.

根据文档，该功能，read_fwf支持dtype属性，但是当我尝试使用它时:

According to the documentation for this function, the dtype attribute is supported in read_fwf, but when I try to use it:

data= pd.io.parsers.read_fwf(file, colspecs = ([79,81], [87,90]), header = None, dtype = {0: np.str, 1: np.str})

我得到了错误:

ValueError: dtype is not supported with python-fwf parser

我尝试过设置"dtype = something"的各种变体，但是它们都返回相同的消息.

I've tried as many variations as I can think of for setting 'dtype = something', but all of them return the same message.

任何帮助将不胜感激！

Any help would be much appreciated!

推荐答案

以@TomAugspurger的示例为基础，为要保留为str的列指定一个转换器，而不是指定dtypes:

Instead of specifying dtypes, specify a converter for the column you want to keep as str, building on @TomAugspurger's example:

from io import StringIO
import pandas as pd
data = StringIO(u"""
121301234
121300123
121300012
""")

pd.read_fwf(data, colspecs=[(0,3),(4,8)], converters = {1: str})

领先

    \n Unnamed: 1
0  121       0123
1  121       0012
2  121       0001

转换器是从列名或索引到用于转换单元格中值的函数的映射(例如，int会将它们转换为整数，将float转换为float等)

Converters are a mapping from a column name or index to a function to convert the value in the cell (eg. int would convert them to integer, float to floats, etc)

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