每次运行python代码时都必须导入excel文件吗？

Question

I'm an R user but trying to learn Python. When using R, once I run a single code to import excel file and save it as dataframe, I was able to use dataframe saved in my working space without re-importing every time.

While using Python, I noticed that unless I use interpreter, I only can run full script(whole "foo.py" file) but not code by code.

I would like to load excel file and work with data inside. My code begins with importing excel file as dataframe. Hence, every time I add new code and want to see the result, I am running all py script and it loads the data every time I run it.

Maybe I am using Python in a wrong way. With Jupyter notebook I didn't have this issue because I was able to run the code cell by cell just like R. But I am trying to use Pycharm now.

import pandas as pd
df = pd.read_excel('foo.xlsx', sheet_name = 'sales_data')
print("Column headings:")
print(df.columns)

Answer 1

Jupyter which runs a script line by line, and you have the variables including the dataframe which has been loaded to memory, so you can use that df until you exit Jupyter .
Whereas an IDE like PyCharm , depending on the edition, especially Community edition runs the whole script in one go, so it needs to load the excel into memory the next time it runs, because it's not persisting any information from the last run.

Jupyter is what we call a REPL , which means all user information is persistent till the session is killed, whereas PyCharm runs all the code in one go while it evauates things line by line, and give you the output at the end.

Answer 2

import pandas as pd

def load_file(file_name,sheetname=None):
    df =     pd.read_excel(file_name, sheet_name =sheetname)
    return df

readed_df = load_file('<file-path>',sheetname='<sheet name>')

then on readed_df to perform rest of task that you want to do .