最新這段時間最學習pandas,這個系列將對pandas的知識點進行總結歸納,趁熱打鐵
###series###
import numpy as np
import pandas as pd
labels = ['a','b','c']
my_list = [10,20,30]
arr = np.array([10,20,30])
d = {'a':10,'b':20,'c':30}
pd.Series(data=my_list)
0 10
1 20
2 30
dtype: int64
pd.Series(data=my_list,index=labels)
a 10
b 20
c 30
dtype: int64
pd.Series(my_list,labels)
a 10
b 20
c 30
dtype: int64
pd.Series(arr)
0 10
1 20
2 30
dtype: int64
pd.Series(arr,labels)
a 10
b 20
c 30
dtype: int64
pd.Series(d)
a 10
b 20
c 30
dtype: int64
pd.Series(data=labels)
0 a
1 b
2 c
dtype: object
pd.Series([sum,print,len])
0 <built-in function sum>
1 <built-in function print>
2 <built-in function len>
dtype: object
ser1 = pd.Series([1,2,3,4],index = ['USA', 'Germany','USSR', 'Japan'])
ser1
USA 1
Germany 2
USSR 3
Japan 4
dtype: int64
ser2 = pd.Series([1,2,5,4],index = ['USA', 'Germany','Italy', 'Japan'])
ser2
USA 1
Germany 2
Italy 5
Japan 4
dtype: int64
ser1['USA']
1
ser1 + ser2
Germany 4.0
Italy NaN
Japan 8.0
USA 2.0
USSR NaN
dtype: float64
s4 = pd.Series([1,2,3,4], index = ['a','b','c','d']
s4
a 1
b 2
c 3
d 4
dtype: int64
s4.values
array([1, 2, 3, 4], dtype=int64)
s4.index
Index([‘a’, ‘b’, ‘c’, ‘d’], dtype=‘object’)
s4['a']
1
s4[s4>2]
c 3
d 4
dtype: int64
s4.to_dict()
{‘a’: 1, ‘b’: 2, ‘c’: 3, ‘d’: 4}
s5 = pd.Series(s4.to_dict())
s5
a 1
b 2
c 3
d 4
dtype: int64