如何有效地遍历 Python 中选定的 Excel 工作表并将它们附加到数据框中？

Question

代替手动输入Excel sheets参数如下：

import pandas as pd

df1 = pd.read_excel(r"C:\Users\XY\Sales2020.xlsm",
                     sheet_name = "Europe",usecols=[1,2,4,6],header=4)      #reads sheet "Europe", selected columns and skips first 4 rows
df1["Continent"]= "Europe"      #adds a new column with sheet name
df1=pd.DataFrame(df1)       #creates df
df1.columns=["ID", "Product", "Quantity","Price","Continent"]   #renames columns in df

df2 = pd.read_excel(r"C:\Users\XY\Sales2020.xlsm",
                     sheet_name = "North America",usecols=[1,2,4,6],header=4)
df2["Continent"]= "North America"
df2=pd.DataFrame(df2)
df2.columns=["ID", "Product", "Quantity","Price","Continent"]

df = pd.concat([df1, df2])     #concats the dfs

我想自动遍历 sheet 并将所有 sheet 中的数据放入数据帧中。我尝试了类似下面的方法，但是它没有完成工作，因为循环只从列表中的最后一个 sheet 获取数据：

import pandas as pd

sheets=["Europe","North America"]

for i in sheets:
    dataset = pd.read_excel(r"C:\Users\XY\Sales2020.xlsm",
                     sheet_name = i,usecols=[1,2,4,6],header=4)     #read Excel
    dataset["Continent"]= i         #adds a new column with sheet name
    dataset = pd.DataFrame(dataset)     #creates df
    dataset.columns=["ID", "Product", "Quantity","Price","Continent"]   #renames columns in df
    df= dataset.append(dataset) #this should append data from sheets into a single df

你有什么想法吗？我该如何解决这个问题？

非常感谢

Answer 1

当数据集已经是数据框时，无需创建新的数据框。

import pandas as pd

sheets=["Europe","North America"]
df_list=[]
for i in sheets:
    dataset = pd.read_excel(r"C:\Users\XY\Sales2020.xlsm",
                     sheet_name = i,usecols=[1,2,4,6],header=4)     #read Excel
    dataset["Continent"]= i         #adds a new column with sheet name
    df_list.append(dataset)
    
 df=pd.concat(df_list)

如何有效地遍历 Python 中选定的 Excel 工作表并将它们附加到数据框中？

How to efficiently iterate through selected Excel sheets in Python and append them into a Data Frame?

python

pandas

dataframe

concat