10 Minutes to pandas
引
By “group by” we are referring to a process involving one or more of the following steps
Splitting the data into groups based on some criteria
Applying a function to each group independently
Combining the results into a data structure
See the Grouping section
代码
df = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo'],
'B': ['one', 'one', 'two', 'three','two', 'two', 'one', 'three'],
'C': np.random.randn(8), 'D': np.random.randn(8)})
print(df)
print(df.groupby('A').sum()) # 计算 foo bar 各自对应 C D 列的和（B列无法求和）
print(df.groupby(['A','B']).sum()) # 同理，不过这里有个一对多的关系
# A B C D
# 0 foo one 0.102071 -0.301926
# 1 bar one 1.161158 0.847451
# 2 foo two -0.023879 0.936338
# 3 bar three -0.353075 -0.834349
# 4 foo two -0.272542 -1.425635
# 5 bar two -1.016016 -0.031614
# 6 foo one -0.428517 0.892747
# 7 foo three -0.843796 0.614443
# /
# C D
# A
# bar -0.207932 -0.018512
# foo -1.466663 0.715967
# C D
# /
# A B
# bar one 1.161158 0.847451
# three -0.353075 -0.834349
# two -1.016016 -0.031614
# foo one -0.326445 0.590821
# three -0.843796 0.614443
# two -0.296421 -0.489296