如何将 Pandas 系列转换为数据框

Question

I've been running some groupings on a dataframe that I have and saving the results in variables. However, I just noticed that the variables are actually being saved as series rather than dataframes.

I've seen tutorials/docs on how to convert a series to a dataframe, but all of them show only static data (by manually typing each of the values into an array), and this isn't an option for me, because I have over 2 million rows in my data frame.

So if I have

TopCustomers = raw_data.groupby(raw_data['Company'])['Total Records'].sum()
Top10Customers = TopCustomers.sort_values().tail(10)

How can I turn Top10Customers into a dataframe? I need it because not all plots work with series.

The syntax frame = { 'Col 1': series1, 'Col 2': series2 } doesn't work because I only have 1 series

Answer 1

Here a small example with data:

import pandas as pd
raw_data = pd.DataFrame({'Company':['A', 'A','B', 'B', 'C', 'C'], 'Total Records':[2,3,6,4,5,10]})
TopCustomers = raw_data.groupby(raw_data['Company'])['Total Records'].sum()

Indeed type(TopCustomers) is pandas.core.series.Series The following turns it in a DataFrame:

pd.DataFrame(TopCustomers)

Otherwise .to_frame() works equally well as indicated above.

Answer 2

您可以使用.to_frame()方法，它将把它变成一个pd.DataFrame 。