如何在熊猫的数据框中读取2列并返回数据列表的列表？

Question

I just started learning pandas and I have a dataframe that looks like

Date        Average    Volume    
2013-02-07    400        4100
2013-02-08    389        3400
2013-02-23    380        3100

If the user says they want the information from the 1st column(I'm referring to the Average here, I am excluding date as its sort of a constant), I want it to return

 ['2013-02-07', 400]
 ['2013-02-08', 389]
 ['2013-02-23', 380]

If they asked for the info from the 2nd column it would return the date and volume info in the same format.

data_list(file_object,column_number)
    inp = int(input('Which column?' ))
    if inp = 1:
        df['Average'].iloc[0:]
    if inp = 2:
        df['Volume'].iloc[0:]

This returns the column the user wants, but how can I return it with the date in the format requested above?

Answer 1

You can use values.tolist

>>> df[['Date','Average']].values.tolist()
[['2013-02-07', 400], ['2013-02-08', 389], ['2013-02-23', 380]]

If you want a generator, you can use map

>>> map(list, df[['Date','Average']].values)
<map object at 0x7f3fd47023c8>
>>> 
>>> [*map(list, df[['Date','Average']].values)]
[['2013-02-07', 400], ['2013-02-08', 389], ['2013-02-23', 380]]

Answer 2

You can precalculate your lists of lists and use a dictionary to store the results. In addition, you can use pd.Series.dt.strftime to format your date as required.

Here's a demo:

df['Date'] = pd.to_datetime(df['Date'])

df_list = {col: df.assign(Date=df.Date.dt.strftime('%Y-%m-%d'))\
                  .loc[:, ['Date', col]].values.tolist() \
                for col in ('Average', 'Volume')}

select = input('Enter a column name:\n')

print(df_list[select])

Example result:

Enter a column name:
Volume
[['2013-02-07', 4100], ['2013-02-08', 3400], ['2013-02-23', 3100]]