【Python】pandas.Series.groupby

官方Pandas庫學習鏈接

import pandas as pd

ser = pd.Series([390., 350., 30., 20.],
                index=['Falcon', 'Falcon', 'Parrot', 'Parrot'],
                name="Max Speed")
print("ser:\n",ser)
print("ser.groupby:\n",ser.groupby(["a", "b", "a", "b"]))
# a = (390+30)/2 = 210 , b = (350+20) / 2 = 185
print("ser.groupby.mean:\n",ser.groupby(["a", "b", "a", "b"]).mean())
print("ser.groupby(level=0).mean():\n",ser.groupby(level=0).mean())
print("ser.groupby(ser > 100):\n",ser.groupby(ser > 100))
print("ser.groupby(ser > 100).mean():\n",ser.groupby(ser > 100).mean())

arrays = [['Falcon', 'Falcon', 'Parrot', 'Parrot'],
          ['Captive', 'Wild', 'Captive', 'Wild']]
index = pd.MultiIndex.from_arrays(arrays, names=('Animal', 'Type'))
ser1 = pd.Series([390., 350., 30., 20.], index=index, name="Max Speed")
print("ser1:\n",ser1)
print("ser1.groupby(level=0).mean():\n",ser1.groupby(level=0).mean())
print("ser1.groupby(level=Type).mean():\n",ser1.groupby(level="Type").mean())