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Dataframe dataframe是一个表格型的数据结构，是一个“带有标签的二维数组” 创立 1、#由数组/list创立，cloums为字典key，index的默觉得数字标签，也可指定 import pandas as pd import numpy as np
data1 = {'a':[1,2,3], 'b':[4,5,6], 'c':[7,8,9]} data2 = {'one':np.random.rand(3), 'two':np.random.rand(3)} d1 = pd.DataFrame(data1) d2 = pd.DataFrame(data2) print(d1) print(d2) d3 = pd.DataFrame(data1,index=list('xyz')) print(d3) # columns可从新指定列 d4 = pd.DataFrame(data2,index=list('qwe'),columns=['one','DD']) print(d4)
------------------------------成果------------------------------- a b c 0 1 4 7 1 2 5 8 2 3 6 9 one two 0 0.038727 0.275714 1 0.886669 0.857068 2 0.881146 0.633808 a b c x 1 4 7 y 2 5 8 z 3 6 9 one DD q 0.038727 NaN w 0.886669 NaN e 0.881146 NaN 2、# Dataframe之由Series创立，columns为字典key，index为Series的标签，若果Series没有标签，则默许数组标签 import pandas as pd import numpy as np
data1 = {'one':pd.Series(np.random.rand(2)), 'two':pd.Series(np.random.rand(3))} data2 = {'one':pd.Series(np.random.rand(2),index = ['a','b']), 'two':pd.Series(np.random.rand(3),index=['a','b','c'])} df1 = pd.DataFrame(data1) df2 = pd.DataFrame(data2) print(df1) print(df2)
----------------------------成果-------------------------- one two 0 0.547841 0.407916 1 0.528967 0.761749 2 NaN 0.638886 one two a 0.462170 0.961833 b 0.508991 0.228698 c NaN 0.306034 3、# Dataframe之由二维创立 import pandas as pd import numpy as np
ar = np.random.rand(9).reshape(3,3) print(ar)
df1 = pd.DataFrame(ar) df2 = pd.DataFrame(ar,index=list('abc'),columns=list('xyz')) print(df1) print(df2)
------------------------------成果------------------------- [[0.11228298 0.74159833 0.32772146] [0.14026585 0.61811644 0.92536378] [0.60881357 0.28399911 0.19018847]] 0 1 2 0 0.112283 0.741598 0.327721 1 0.140266 0.618116 0.925364 2 0.608814 0.283999 0.190188 x y z a 0.112283 0.741598 0.327721 b 0.140266 0.618116 0.925364 c 0.608814 0.283999 0.190188 4、# 由字典构成的列表创立,columns为字典的key，index不指定默觉得数组标签 import pandas as pd import numpy as np
data = [{'one':1,'two':2},{'one':5,'two':10,'three':20}] print(data) df1 = pd.DataFrame(data) df2 = pd.DataFrame(data,index=['a','b'],columns=['one','big']) print(df1) print(df2)
-----------------------------成果----------------------------- [{'one': 1, 'two': 2}, {'one': 5, 'two': 10, 'three': 20}] one three two 0 1 NaN 2 1 5 20.0 10 one big a 1 NaN b 5 NaN 5、# 由字典构成的字典创立,colums为字典的key，index为自定的key，这里的index不能改变 import pandas as pd import numpy as np
data = [{'one':1,'two':2},{'one':5,'two':10,'three':20}] print(data) df1 = pd.DataFrame(data) df2 = pd.DataFrame(data,index=['a','b'],columns=['one','big']) print(df1) print(df2)
-------------------------------成果------------------------------- {'Jack': {'math': 90, 'english': 80, 'art': 88}, 'Marry': {'math': 80, 'english': 70, 'art': 100}, 'Tom': {'math': 80, 'english': 70}} Jack Marry Tom art 88 100 NaN english 80 70 70.0 math 90 80 80.0 Tom Jack Bob art NaN 88 NaN english 70.0 80 NaN math 80.0 90 NaN Jack Marry Tom a NaN NaN NaN b NaN NaN NaN c NaN NaN NaN
--------------------- 作者：weixin_40027906 起源：CSDN 原文：https://blog.csdn.net/weixin_40027906/article/details/90321359 版权申明：本文为博主原创文章，转载请附上博文链接！ |