Dataframe groupby to count frequency and write to Excel

Question

A data-frame that I want to do some Excel pivot-table alike summary, like the screenshot below.

import pandas as pd

data = {'People' : ["David","Kate","Kate","Kate","David","David","Kate","David","Kate"],
'Year': ["2016","2016","2016","2017","2017","2017","2016","2017","2016"],
'Project' : ["TN","DM","TN","DM","DJ","DM","DM","DM","TN"]}

df = pd.DataFrame(data)

df_1 = df.groupby(['People', 'Year', 'Project'])["Project"].count()

df_1 output as below:

Then I want to export all with no blank cells to Excel spreadsheet.

df_1.reset_index().to_excel('file.xlsx', index=False)

But it gives me error:

ValueError: cannot insert Project, already exists

I tried below also doesn't work:

df_1.reset_index().to_excel('file.xlsx', index=False)

What's the right way to write it? Thank you.

Answer 1

Try this:

df_1 = df.groupby(['People', 'Year', 'Project'])["Project"].count().reset_index(name="count")
df_1.to_excel('file.xlsx')