python dataframe水平附加列

Question

I am trying to make a simple script that concatenates or appends multiple column sets that I pull from xls files within a directory. Each xls file has a format of:

Index    Exp. m/z   Intensity   
1        1000.11    1000
2        2000.14    2000
3        3000.15    3000

Each file has varying number of indices. Below is my code:

import pandas as pd
import os
import tkinter.filedialog

full_path = tkinter.filedialog.askdirectory(initialdir='.')
os.chdir(full_path)

data = {}
df = pd.DataFrame()

for files in os.listdir(full_path):
    if os.path.isfile(os.path.join(full_path, files)):
        df = pd.read_excel(files, 'Sheet1')[['Exp. m/z', 'Intensity']]
        data = df.concat(df, axis=1)

data.to_excel('test.xls', index=False)

This produces an attributerror: DataFrame object has no attribute concat. I also tried using append like:

data = df.append(df, axis=1) 

but I know that append has no axis keyword argument. df.append(df) does work, but it places the columns at the bottom. I want something like:

Exp. m/z   Intensity       Exp. m/z   Intensity  
1000.11    1000            1001.43    1000
2000.14    2000            1011.45    2000
3000.15    3000

and so on. So the column sets that I pull from each file should be placed to the right of the previous column sets, with a column space in between.

Answer 1

I think you need append DataFrames to list and then pd.concat :

dfs = []
for files in os.listdir(full_path):
    if os.path.isfile(os.path.join(full_path, files)):
        df = pd.read_excel(files, 'Sheet1')[['Exp. m/z', 'Intensity']]
        #for add empty column 
        df['empty'] = np.nan
        dfs.append(df)
data = pd.concat(dfs, axis=1)