2.



In [1]:

    
import pandas as pd



In [5]:

    
import datetime



In [2]:

    
data = pd.read_table('daily_weather.tsv')

convert date column to a datetime object



In [8]:

    
for i, row in enumerate(data['date']):
        data.set_value(i, 'date', datetime.datetime.strptime(row, '%Y-%m-%d').date())

make a column for the month



In [10]:

    
for i, row in enumerate(data['date']):
    data.set_value(i, 'month', row.month)

sort by month column, print the mean of the temp column



In [12]:

    
data.groupby('month')['temp'].mean()









    Out[12]:





month
1     0.275181
2     0.315337
3     0.449411
4     0.468809
5     0.612366
6     0.675111
7     0.752366
8     0.711801
9     0.620083
10    0.500049
11    0.336101
12    0.322880
Name: temp, dtype: float64