使用不同的输入多次运行 Python 脚本

Question

I am new to programming.

My script does the following:

1. Converts single Excel sheet into single CSV file

2. Opens that CSV file and adds new column with number and saves it

import pandas as pd

data_xls = pd.read_excel('excel_file.xlsx', ' tab_name ', index_col=None)
data_xls.to_csv('tab_name.csv', encoding='utf-8', index=False)
data_csv = pd.read_csv('tab_name.csv')
data_csv.insert(0, 'new_column_header', range(1, 1 + len(df)))
data_csv.to_csv('tab_name.csv', index=False )

My challenge:

Excel document consists of multiple sheets (tabs) let's say: "tab1, tab2, tab3".

I need guidance how to run the same script in a loop over multiple tabs (ie list).

Answer 1

One way is to hard-code your tab names in a list and loop over them.

for tab in ["tab1", "tab2", "tab3"]:
    data_xls = pd.read_excel('excel_file.xlsx', tab, index_col=None)
    data_xls.to_csv(tab + '.csv', encoding='utf-8', index=False)
    data_csv = pd.read_csv(tab + '.csv')
    data_csv.insert(0, 'new_column_header', range(1, 1 + len(df)))
    data_csv.to_csv(tab + '.csv', index=False )

Answer 2

Here is what you need:

dict_dfs = pd.read_excel("file.xlsx", sheet_name=None)

This will return you an OrderedDict whose keys will be the sheet names and values will be dataframes.

All you need is to loop over and do your manipulations and then save the individual dataframes as csv.

for k in dict_dfs:
    # your processing here
    dict_dfs[k].to_csv("custom_filename_for_each_dataframe.csv")

Hope this helps.