u010376229的博客

1、map创建一个Series>>> s = pd.Series(['cat', 'dog', np.nan, 'rabbit'])>>> s0 cat1 dog2 NaN3 rabbitdtype: object根据字典值做映射，如果值不在字典里，会转换成NaN>>> s.map({'cat': 'kitten', 'dog': 'puppy'})0 kitten1 puppy2

import numpy as np# 生成10行4列的array，数据范围为0-100的整数nd = np.random.randint(0, 100, size=(10, 4))print(nd)'''array([[68, 0, 98, 11], [27, 38, 37, 59], [11, 45, 27, 2], [37, 74, 76, 90], [53, 66, 10, 25], [64, 88, 34, 74]

import pandas as pdimport numpy as np# 生成10行4列的dataFrame，数据为在0-100范围内的随机数df = pd.DataFrame(np.random.randint(0, 100, size=(10, 4)))print(df)'''df 0 1 2 30 50 79 26 891 53 56 31 422 75 82 85 763 92 17 97 654 9 80 18