如何将所有 csv 文件合并为一个文件并将数据堆叠在原始标题下？

如何解决如何将所有 csv 文件合并为一个文件并将数据堆叠在原始标题下？

我是 Python 新手，正在尝试了解数据操作。

我有一个包含多个文件的文件夹。其中一些是csv。我想合并所有的 csvs - 其中大约 400 个到一个单独的 csv 和所有要堆叠的数据

例如，如果第一个 csv 有一个数据框-

transcript  confidence  from    to  speaker Negative Neutral    Positive    compound
thank you   0.85    1.39    1.65    0   0   0.754              0.246         0.7351

second 有一个数据框：

 transcript confidence  from    to  speaker Negative Neutral    Positive compound
    welcome     0.95       1.39   1.65  0   0       0.754        0.201   0.8351

我希望最终的 df 看起来像 -

transcript  confidence from to  speaker Negative Neutral      Positive       compound
thank you   0.85      1.39  1.65    0   0       0.754              0.246         0.7351
welcome     0.95      1.39  1.65    0   0       0.754              0.201         0.8351

我试过了-

import glob
import pandas as pd

# Folder containing the .csv files to merge
file_path = "C:\\Users\\Desktop"

# This pattern \\* selects all files in a directory
pattern = file_path + "\\*"
files = glob.glob(pattern)

# Import first file to initiate the dataframe
df = pd.read_csv(files[0],encoding = "utf-8",delimiter = ",")

# Append all the files as dataframes to the first one
for file in files[1:len(file_list)]:
    df_csv = pd.read_csv(file,")
    df = df.append(df_csv)

但是没有用。我该如何解决这个问题？

解决方法

这应该会有所帮助：

import pandas as pd
import glob
import os.path

file_path = "C:/Users/Desktop"

data = []
for csvfile in glob.glob(os.path.join(file_path,"*.csv")):
    df = pd.read_csv(csvfile,encoding="utf-8",delimiter=",")
    data.append(df)

data = pd.concat(data,ignore_index=True)

,

注意：-我会建议您而不是从桌面获取所有 CSV 文件。请将其保存到一个目录，如果您以后想分析该特定数据集，这也将很有帮助。

解决方案前的基本要求：-所有要合并的 CSV 文件都应该在同一目录中。

# Import all Important Libraries

# 'os' module will provide a portable way of using an operating system with dependent functionality such as 'Open File',and much more...
import os

# 'glob' module helps to find all the pathnames matched with a specified pattern according to the rules. Such as '*.csv' which is used in our case for finding all CSV Files
import glob

# 'pandas' is a fast,powerful,flexible,and easy to use open-source data analysis and manipulation tool
import pandas as pd

# First of all declare 'path' variable for finding all the CSV  
path = "C:/Users/Desktop"

# Store all files in 'all_files' using 'glob' function. and a pattern used is '*.csv' Which will find all the CSV and 'join' it
all_files = glob.glob(os.path.join(path,"*.csv"))

# Initialize 'DataFrame' Variable from each fetched CSV file
df_from_each_file = (pd.read_csv(csvfiles) for csvfiles in all_files) 
# if you have 'Seperator' then use 'pd.read_csv(csvfiles,sep='seprator pattern ('\',',etc.)')' in above code

# Concat all the 'DataFrame' using 'pd.concat()'
df_merged   = pd.concat(df_from_each_file,ignore_index=True)

# Store Merged CSV Files into 'merged.csv' File
df_merged.to_csv("merged.csv")