python - 如何循环导入多个 .txt 文件但不串联？

Question

我在 .txt(以空格分隔)中有许多(>40)数据文件，它们具有相同的布局，我想将它们读入 python 中进行数据处理和绘图。这些文件是一个参数的参数化扫描的模型输出，该参数在每个数据文件中占据一列。该参数递增到每个连续文件中的下一个值。

我遇到的问题是我不知道如何编写 for 循环来将每个数据文件读取到自己的数据帧中。

我看到很多答案建议“pandas.read_csv”然后串联，但是我不想将文件连接到一个数据帧中，因为我想单独绘制每个数据集。对我来说，仅仅为了随后分离出数据集而诉诸连接数据框是没有意义的。

import glob
import os
import pandas as pd
from pandas import Series, DataFrame

path = r'D:/user/data-folder/'

files = glob.glob(os.path.join(path + 'data-*.txt')) # Added based on suggestions from similar questions
df1 = []
for f in files:
    df = pd.read_csv(path1 + f,
         sep=' '
         )
    df1.append(df)

print(df1)

理想情况下，我希望将每个数据文件读入自己的数据帧中，并递增编号，例如“df1_1”、“df1_2”等然后，我可以单独操作每个数据帧，并将数据相互绘制以进行比较。

Answer 1

数据框列表怎么样？如果您有:

../data/a.txt:

firstname,lastname,hobby
niles,crane,wine tasting
martin,crane,sitting in recliner
bob,bulldog,being annoying

../data/b.txt:

firstname,lastname,hobby
john,doe,doing stuff
jane,doe,being anonymous
humphrey,bogart,smoking and drinking

代码:

def main():

    from glob import glob
    from os.path import join
    import pandas as pd
    from pandas import DataFrame
    from contextlib import ExitStack

    local_path = "data/"

    filenames = glob(join(local_path + "*.txt"))

    with ExitStack() as context_manager:
        files = [context_manager.enter_context(open(filename, "r")) for filename in filenames]

        dataframes = []
        for file in files:
            dataframe = pd.read_csv(file)
            dataframes.append(dataframe)

        print(dataframes[0], end="\n\n")
        print(dataframes[1])

    return 0


if __name__ == "__main__":
    import sys
    sys.exit(main())

输出:

  firstname lastname                hobby
0     niles    crane         wine tasting
1    martin    crane  sitting in recliner
2       bob  bulldog       being annoying

  firstname lastname                 hobby
0      john      doe           doing stuff
1      jane      doe       being anonymous
2  humphrey   bogart  smoking and drinking