pandas设置值更改值
Posted 棍子哥
tags:
篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了pandas设置值更改值相关的知识，希望对你有一定的参考价值。
#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2018/5/24 15:03 # @Author : zhang chao # @File : s.py from scipy import linalg as lg #按标签选择 #通过标签选择多轴 import pandas as pd import numpy as np dates = pd.date_range(‘20170101‘, periods=8) df = pd.DataFrame(np.random.randn(8,4), index=dates, columns=list(‘ABCD‘)) print("df:") print(df) print(‘-‘*50) s=pd.Series(list(range(10,18)),index=pd.date_range(‘20170101‘, periods=8)) df["F"]=s#新加一列元素F print("df[‘F‘]=s") print(df) print(‘-‘*50) df.at[dates[0],"A"]=99 print("df.at[dates[0],‘A‘]=99") print(df) print(‘-‘*50) print("df.iat[1,1]=-66") df.iat[1,1]=-66 print(df) print(‘-‘*50) print("df.loc[:,‘D‘]=np.array([4]*len(df))") df.loc[:,"D"]=np.array([4]*len(df)) print(df) print(‘-‘*50) df2=df.copy()#拷贝 print(‘-‘*50) print("") df2[df2>0]=-df2#将df2中的所有大于0的元素值 都改为小于0的 print (df2)
D:\Download\python3\python3.exe D:/Download/pycharmworkspace/s.py df: A B C D 2017-01-01 -0.598774 1.076390 -0.642006 -0.089715 2017-01-02 -0.438976 1.063627 0.387825 1.312049 2017-01-03 0.101879 0.469225 0.860522 0.086417 2017-01-04 -0.670031 1.974935 -0.570337 0.478371 2017-01-05 0.250046 -1.385470 -0.893637 -1.786031 2017-01-06 0.876446 -0.167285 -0.475356 -0.145381 2017-01-07 0.291258 0.676994 -1.953909 -0.609507 2017-01-08 -0.569716 0.749637 1.038614 -0.502682 -------------------------------------------------- df[‘F‘]=s A B C D F 2017-01-01 -0.598774 1.076390 -0.642006 -0.089715 10 2017-01-02 -0.438976 1.063627 0.387825 1.312049 11 2017-01-03 0.101879 0.469225 0.860522 0.086417 12 2017-01-04 -0.670031 1.974935 -0.570337 0.478371 13 2017-01-05 0.250046 -1.385470 -0.893637 -1.786031 14 2017-01-06 0.876446 -0.167285 -0.475356 -0.145381 15 2017-01-07 0.291258 0.676994 -1.953909 -0.609507 16 2017-01-08 -0.569716 0.749637 1.038614 -0.502682 17 -------------------------------------------------- df.at[dates[0],‘A‘]=99 A B C D F 2017-01-01 99.000000 1.076390 -0.642006 -0.089715 10 2017-01-02 -0.438976 1.063627 0.387825 1.312049 11 2017-01-03 0.101879 0.469225 0.860522 0.086417 12 2017-01-04 -0.670031 1.974935 -0.570337 0.478371 13 2017-01-05 0.250046 -1.385470 -0.893637 -1.786031 14 2017-01-06 0.876446 -0.167285 -0.475356 -0.145381 15 2017-01-07 0.291258 0.676994 -1.953909 -0.609507 16 2017-01-08 -0.569716 0.749637 1.038614 -0.502682 17 -------------------------------------------------- df.iat[1,1]=-66 A B C D F 2017-01-01 99.000000 1.076390 -0.642006 -0.089715 10 2017-01-02 -0.438976 -66.000000 0.387825 1.312049 11 2017-01-03 0.101879 0.469225 0.860522 0.086417 12 2017-01-04 -0.670031 1.974935 -0.570337 0.478371 13 2017-01-05 0.250046 -1.385470 -0.893637 -1.786031 14 2017-01-06 0.876446 -0.167285 -0.475356 -0.145381 15 2017-01-07 0.291258 0.676994 -1.953909 -0.609507 16 2017-01-08 -0.569716 0.749637 1.038614 -0.502682 17 -------------------------------------------------- df.loc[:,‘D‘]=np.array([4]*len(df)) A B C D F 2017-01-01 99.000000 1.076390 -0.642006 4 10 2017-01-02 -0.438976 -66.000000 0.387825 4 11 2017-01-03 0.101879 0.469225 0.860522 4 12 2017-01-04 -0.670031 1.974935 -0.570337 4 13 2017-01-05 0.250046 -1.385470 -0.893637 4 14 2017-01-06 0.876446 -0.167285 -0.475356 4 15 2017-01-07 0.291258 0.676994 -1.953909 4 16 2017-01-08 -0.569716 0.749637 1.038614 4 17 -------------------------------------------------- -------------------------------------------------- A B C D F 2017-01-01 -99.000000 -1.076390 -0.642006 -4 -10 2017-01-02 -0.438976 -66.000000 -0.387825 -4 -11 2017-01-03 -0.101879 -0.469225 -0.860522 -4 -12 2017-01-04 -0.670031 -1.974935 -0.570337 -4 -13 2017-01-05 -0.250046 -1.385470 -0.893637 -4 -14 2017-01-06 -0.876446 -0.167285 -0.475356 -4 -15 2017-01-07 -0.291258 -0.676994 -1.953909 -4 -16 2017-01-08 -0.569716 -0.749637 -1.038614 -4 -17 Process finished with exit code 0
以上是关于pandas设置值更改值的主要内容，如果未能解决你的问题，请参考以下文章