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.
Requirements and Background information:
- 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
Here is one sample *.txt file. All the others have the same format.
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:
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:
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?