技術標籤：Python3pythonnumpypandas

Series是隻能儲存相同的資料型別。
One-dimensional ndarray with axis labels (including time series).

import pandas as pd
import numpy as np

labels = ['a','b','c']
my_data = [10,20,30]
arr = np.array(my_data)
d = {'a':10, 'b':20, 'c':30}

print(pd.Series(data = my_data))
print(pd.Series(
 
data = labels))
print(pd.Series(data = d))
print(pd.Series(data = arr))

print("**************")

print(pd.Series(my_data, labels))
print(pd.Series(data = my_data, index=labels))

print("**************")
print(pd.Series(data = labels, index=labels))
print(pd.Series(data = d, index=
 
labels))

print("**************")
print(pd.Series([sum,print,len]))
print("***************")

# index的數目必須跟data的數目一致，不然會出錯
print(pd.Series([1,2,3,4],['adsfs','sdfsf','werew','sdfsf']))
print(pd.Series([1,2,5,4],['adsfs','sdfsf','werew','sdfsf']))
print(pd.Series([1,2,3,4],['adsfs'
 
,'sdfsf','werew','sdfsf']) + pd.Series([1,2,5,4],['adsfs','sdfsf','werew','sdfsf']))
print(pd.Series([1,2,5,4],['adsfs','sdfsf','werew','sdfsf'])['adsfs'])

print("****************")
print(pd.Series(data=labels))
print(pd.Series(data=labels)[0])

結果如下：


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