如何从txt文件创建csv文件，并在"x“字符后使用列分隔符

Question

我有一个txt文件，如下所示：

MT0111500000000 Anniston-Oxford-Jacksonville, AL Metropolitan Statistical Area
MT0112220000000 Auburn-Opelika, AL Metropolitan Statistical Area  
MT0113820000000 Birmingham-Hoover, AL Metropolitan Statistical Area

我需要从这里创建一个csv文件，我在这方面的经验很少，但我一直在学习和做它，尽管可能效率不高。

我现在的问题是，当我使用pandas时，它会在"，“之后创建列。我需要的是左侧代码"MT0113820000000“后面的列分隔符，尽管代码确实发生了变化，但它们的长度都是相同的。

提前谢谢，我知道这是一个很难回答的问题。

下面是我目前的代码：

import pandas as pd

dataframe1 = pd.read_csv("C:/Users/andre/Desktop/bea_api_test/python-bureau-economic-analysis-api-client/testttt/output.txt")  
dataframe1.to_csv('output_.csv', index = None)

和输出：

COLUMN 1                                COLUMN 2
MT0111500000000 Anniston-Oxford-Jacksonville     | AL Metropolitan Statistical Area

Answer 1

或者，使用上面注释中提到的read_fwf：

from io import StringIO
import pandas as pd

testdata = '''\
MT0111500000000 Anniston-Oxford-Jacksonville, AL Metropolitan Statistical Area
MT0112220000000 Auburn-Opelika, AL Metropolitan Statistical Area
MT0113820000000 Birmingham-Hoover, AL Metropolitan Statistical Area
'''

buff = StringIO(testdata)

df = pd.read_fwf(buff, header=None, colspecs=[(0, 15), (16, 64 * 1024)])

print(df.to_csv(index=False, columns=[0, 1], header=['COLUMN1', 'COLUMN2']))

Answer 2

这不是CSV，我也看不到说服read_csv做正确事情的便捷方法。幸运的是，这里似乎有一条简单的规则。第一个空格之前的东西，然后是后面的东西。str.split就是这么做的。

import pandas as pd
from pathlib import Path

#in_file = Path("C:/Users/andre/Desktop/bea_api_test/python-bureau-economic-analysis-api-client/testttt/output.txt")
in_file = Path("test.txt")
out_file = in_file.with_name(in_file.stem + "_").with_suffix(".csv")

    # test data
    open(in_file, "w").write("""\
    MT0111500000000 Anniston-Oxford-Jacksonville, AL Metropolitan Statistical Area
    MT0112220000000 Auburn-Opelika, AL Metropolitan Statistical Area  
    MT0113820000000 Birmingham-Hoover, AL Metropolitan Statistical Area""")
    
    # convert to csv
    pd.DataFrame([line.strip().split(" ",1) for line in open(in_file)],
        columns=["COLUMN1", "COLUMN2"]).to_csv(out_file, index=None, headr=False)
    
    # visual verification
    print(open(out_file).read())

输出

MT0111500000000,"Anniston-Oxford-Jacksonville, AL Metropolitan Statistical Area"
MT0112220000000,"Auburn-Opelika, AL Metropolitan Statistical Area"
MT0113820000000,"Birmingham-Hoover, AL Metropolitan Statistical Area"

在本例中，我立即编写了csv，这样数据帧就会自动从内存中删除。您也可以使用CSV模块执行此操作，一次编写一行代码。这将使用较少的内存，因为它不必在内存中保存整个文件。由于csv是标准python库的一部分，因此对pandas没有外部依赖。添加一些文件名处理

import csv
from pathlib import Path

#in_file = Path("C:/Users/andre/Desktop/bea_api_test/python-bureau-economic-analysis-api-client/testttt/output.txt")
in_file = Path("test.txt")
out_file = in_file.with_name(in_file.stem + "_").with_suffix(".csv")

# test data
open(in_file, "w").write("""\
MT0111500000000 Anniston-Oxford-Jacksonville, AL Metropolitan Statistical Area
MT0112220000000 Auburn-Opelika, AL Metropolitan Statistical Area  
MT0113820000000 Birmingham-Hoover, AL Metropolitan Statistical Area""")

# convert to csv
with open(in_file) as infp, open(out_file, "w") as outfp:
    writer = csv.writer(outfp)
    writer.writerows(line.strip().split(" ",1) for line in infp)

# visual verification
print(open(out_file).read())

Answer 3

您可以在第一次出现空格时拆分数据：

data = pd.read_table("data.txt", squeeze = True, header = None).str.split(" ", 1)
df = pd.DataFrame(data.tolist(), columns = ["column1", "column2"])

df.to_csv("df.csv")