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.
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)
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