[ Python 常見問題 ] Pandas - Groupby: Count and mean combined

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Question
Working with PANDAS to try and summarise a dataframe as a count of certain categories, as well as the means sentiment score for these categories. There is table full of strings which have different sentiment scores, and I want to group each text source by saying how many posts they have, as well as the average sentiment of these posts.

My (simplified) dataframe looks like this:

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1. import pandas as pd  
2. import numpy as np  
3.   
4. df = pd.DataFrame(data=[  
5.     ['bar', 'some string', 0.13],  
6.     ['foo', 'alt string',  -0.8],  
7.     ['bar', 'another str',  0.7],  
8.     ['foo', 'some text',   -0.2],  
9.     ['foo', 'more text',   -0.5]],  
10.     columns=['source', 'text', 'sent']  
11. )  

My expected output will look like this:

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1. source    count     mean_sent  
2. -----------------------------  
3. foo       3         -0.5  
4. bar       2         0.415  

HowTo
You can use groupby with aggregate:

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1. df.groupby('source') \  
2.        .agg({'text':'size', 'sent':'mean'}) \  
3.        .rename(columns={'text':'count','sent':'mean_sent'}) \  
4.        .reset_index()