pandas将Series转成DataFrame的实现

import pandas as pd

department = ['A', 'A', 'A', 'B', 'B', 'B', 'C', 'C']
group = ['g1', 'g1', 'g2', 'g3', 'g3', 'g4', 'g5', 'g5']
data = pd.DataFrame({'department': department, 'group': group})

d2 = data.groupby('department')['group'].apply(lambda x: ",".join(x))
print("d2 is: ", '\n', d2, "\nd2 type is: ", type(d2), '\n')
d2 = pd.DataFrame({'department': d2.index, 'group': d2.values})
print("after change, d2 is: ", '\n', d2, '\nd2 type is: ', type(d2), '\n')

d2 is:  
 department
A    g1,g1,g2
B    g3,g3,g4
C       g5,g5
Name: group, dtype: object 
d2 type is:  <class 'pandas.core.series.Series'> 

after change, d2 is:  
   department     group
0          A  g1,g1,g2
1          B  g3,g3,g4
2          C     g5,g5 
d2 type is:  <class 'pandas.core.frame.DataFrame'> 

d3 = data.groupby('department')['group'].apply(lambda x: ','.join(x))
d3 = d3.reset_index(name='group')
d3['group'] = d3['group'].map(lambda x: ','.join(sorted(list(set(x.split(','))))))
print(d3)

import pandas as pd

a = [1, 2, 3, 4, 5]
b = [10, 20, 30, 40, 50]
c = [0.1, 0.2, 0.3, 0.4, 0.5]

data = pd.DataFrame({'a': a, 'b': b, 'c': c})
print(data.apply(max), '\n')
print(data.a.apply(lambda x: x * 2), '\n')

print(data.applymap(lambda x: x+0.01), '\n')

print(data.a.map(lambda x: x+0.02))

a     5.0
b    50.0
c     0.5
dtype: float64 

0     2
1     4
2     6
3     8
4    10
Name: a, dtype: int64 

      a      b     c
0  1.01  10.01  0.11
1  2.01  20.01  0.21
2  3.01  30.01  0.31
3  4.01  40.01  0.41
4  5.01  50.01  0.51 

0    1.02
1    2.02
2    3.02
3    4.02
4    5.02
Name: a, dtype: float64