读取 python 中的多个 excel 文件

Question

Sample data image I'm new to python. Trying to read multiple excel files in folder and make it separate DataFrames.

Is the below code correct?

import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import sys, os
import matplotlib.pyplot as plt 
from sklearn.model_selection import train_test_split
os.chdir(r'/Users/try/Documents/data')

df = ([])
def readdataframe(the_list):
    for element in the_list:
        print(element)
        df[element] = pd.read_excel(element, 'shee1')

readdataframe(["24032020_D_KWH.xlsx","25032020_D_KWH.xlsx","26032020_D_KWH.xlsx","27032020_D_KWH.xlsx"])

I get below error when I execute

TypeError: list indices must be integers or slices, not str

Answer 1

Changing df = ([]) with df=pd.DataFrame() should do the trick. You didn't define your df as a pandas dataframe.

After a test this is what I came up with:

import pandas as pd
import os

os.chdir(r"path to your excel files")

the_list = []

for root, dirs, files in os.walk(r"path to your excel files"):
    for file in files:
        if file.endswith('.xlsx'):
            the_list.append(file)

def readdataframe(the_list):
    df = pd.DataFrame() #define df as an empty pandas DataFrame
    for element in the_list:
        #print(element)
        df[element] = pd.read_excel(element, squeeze=True)
    return df

print(readdataframe(the_list))

Output:

   file1.xlsx  file2.xlsx  file3.xlsx
0           1           6          11
1           2           7          12
2           3           8          13
3           4           9          14
4           5          10          15

I'm sorry but it is considered a bad practice to upload your files, and I'm not going to download it. Nothing personal, just basic digital hygiene.

Now onto the explanation. As you may have noticed in this line

df[element] = pd.read_excel(element, squeeze=True)

I"ve added

squeeze=True

What this parameter does is convert the dataframe that was returned into a pandas Series (one-dimensional array, think of it as your general python list), because I had only 1 column in each of my files and

df[element] =

syntax sets "element" as a column name in your dataframe where you save your data. So, this way will only work if data in your file is one-dimensional (only 1 column) If not, you should probably look into pandas.concat or pandas DataFrame join depending on the uniformity of the data shape in the files and your needs.

if you are willing to get multiple dataframes instead this is what I'm suggesting.

import pandas as pd
import os

os.chdir(r"path to your excel files")

the_list = []

for root, dirs, files in os.walk(r"path to your excel files"):
    for file in files:
        if file.endswith('.xlsx'):
            the_list.append(file)

def readdataframe(the_list):
    df_dict = {}
    for element in the_list:
        df_dict[element] = pd.read_excel(element)
    return df_dict

print(readdataframe(the_list))

This way you are getting a python dictionary(hashtable) that contains your dataframe objects as a value and filename as a key.