以文件名作为列标题将多个 *.txt 文件读入 Pandas Dataframe
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Read multiple *.txt files into Pandas Dataframe with filename as column header
提问by edesz
I am trying to import a set of *.txt files. I need to import the files into successive columns of a Pandas DataFrame in Python.
我正在尝试导入一组 *.txt 文件。我需要将文件导入 Python 中 Pandas DataFrame 的连续列中。
Requirements and Background information:
要求和背景信息：
- Each file has one column of numbers
- No headers are present in the files
- Positive and negative integers are possible
- The size of all the *.txt files is the same
- The columns of the DataFrame must have the name of file (without extension) as the header
- The number of files is not known ahead of time
- 每个文件都有一列数字
- 文件中不存在标题
- 正整数和负整数都是可能的
- 所有 *.txt 文件的大小相同
- DataFrame 的列必须以文件名（不带扩展名）作为标题
- 提前不知道文件数量
Here is one sample *.txt file. All the others have the same format.
这是一个示例 *.txt 文件。所有其他人都具有相同的格式。
16
54
-314
1
15
4
153
86
4
64
373
3
434
31
93
53
873
43
11
533
46
Here is my attempt:
这是我的尝试：
import pandas as pd
import os
import glob
# Step 1: get a list of all csv files in target directory
my_dir = "C:\Python27\Files\"
filelist = []
filesList = []
os.chdir( my_dir )
# Step 2: Build up list of files:
for files in glob.glob("*.txt"):
fileName, fileExtension = os.path.splitext(files)
filelist.append(fileName) #filename without extension
filesList.append(files) #filename with extension
# Step 3: Build up DataFrame:
df = pd.DataFrame()
for ijk in filelist:
frame = pd.read_csv(filesList[ijk])
df = df.append(frame)
print df
Steps 1 and 2 work. I am having problems with step 3. I get the following error message:
步骤 1 和 2 起作用。我在执行第 3 步时遇到问题。我收到以下错误消息：
Traceback (most recent call last):
File "C:\Python27\TextFile.py", line 26, in <module>
frame = pd.read_csv(filesList[ijk])
TypeError: list indices must be integers, not str
Question: Is there a better way to load these *.txt files into a Pandas dataframe? Why does read_csv not accept strings for file names?
问题：有没有更好的方法将这些 *.txt 文件加载到 Pandas 数据框中？为什么 read_csv 不接受文件名的字符串？
回答by CT Zhu
You can read them into multiple dataframes and concat them together afterwards. Suppose you have two of those files, containing the data shown.
您可以将它们读入多个数据帧，然后将它们连接在一起。假设您有其中两个文件，其中包含显示的数据。
In [6]:
filelist = ['val1.txt', 'val2.txt']
print pd.concat([pd.read_csv(item, names=[item[:-4]]) for item in filelist], axis=1)
val1 val2
0 16 16
1 54 54
2 -314 -314
3 1 1
4 15 15
5 4 4
6 153 153
7 86 86
8 4 4
9 64 64
10 373 373
11 3 3
12 434 434
13 31 31
14 93 93
15 53 53
16 873 873
17 43 43
18 11 11
19 533 533
20 46 46
回答by Kracit
You're very close. ijkis the filename already, you don't need to access the list:
你很亲近。ijk已经是文件名，您不需要访问列表：
# Step 3: Build up DataFrame:
df = pd.DataFrame()
for ijk in filelist:
frame = pd.read_csv(ijk)
df = df.append(frame)
print df
# Step 3: Build up DataFrame:
df = pd.DataFrame()
for ijk in filelist:
frame = pd.read_csv(ijk)
df = df.append(frame)
print df
In the future, please provide working code exactly as is. You import from pandas import *yet then refer to pandas as pd, implying the import import pandas as pd.
将来，请完全按原样提供工作代码。您导入from pandas import *然后将Pandas称为 pd，暗示 import import pandas as pd。
You also want to be careful with variable names. filesis actually a single file path, and filelistand filesListhave no discernible difference from the variable name. It also seems like a bad idea to keep personal documents in your python directory.
您还需要注意变量名称。files实际上是单个文件路径，并且filelist与filesList变量名称没有明显区别。将个人文档保存在 python 目录中似乎也是一个坏主意。
