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导入支持包
import pandas as pd import numpy as np
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生成测试数据
dates = pd.date_range('20200218', periods=6) df = pd.DataFrame(np.arange(24).reshape((6,4)),index=dates, columns=['A','B','C','D']) ''' A B C D 2020-02-18 0 1 2 3 2020-02-19 4 5 6 7 2020-02-20 8 9 10 11 2020-02-21 12 13 14 15 2020-02-22 16 17 18 19 2020-02-23 20 21 22 23 '''
注:下面所有的操作都是基于这里的原始数据
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根据序数索引和属性索引设置值
df.iloc[2,2] = 1111 df.loc['20200220','B'] = 2222 ''' A B C D 2020-02-18 0 1 2 3 2020-02-19 4 5 6 7 2020-02-20 8 2222 1111 11 2020-02-21 12 13 14 15 2020-02-22 16 17 18 19 2020-02-23 20 21 22 23 '''
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根据是否满足条件设置值
df.B[df.A>4] = 0 ''' A B C D 2020-02-18 0 1 2 3 2020-02-19 4 5 6 7 2020-02-20 8 0 10 11 2020-02-21 12 0 14 15 2020-02-22 16 0 18 19 2020-02-23 20 0 22 23 '''
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设置整列的值
df['F'] = 8888 ''' A B C D F 2020-02-18 0 1 2 3 8888 2020-02-19 4 5 6 7 8888 2020-02-20 8 9 10 11 8888 2020-02-21 12 13 14 15 8888 2020-02-22 16 17 18 19 8888 2020-02-23 20 21 22 23 8888 '''
df['E'] = pd.Series([1,2,3,4,5,6], index=pd.date_range('20200218',periods=6)) # A B C D E # 2020-02-18 0 1 2 3 1 # 2020-02-19 4 5 6 7 2 # 2020-02-20 8 9 10 11 3 # 2020-02-21 12 13 14 15 4 # 2020-02-22 16 17 18 19 5 # 2020-02-23 20 21 22 23 6
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参考文献
程序主要来自 Pandas 设置值,略有改动
Pandas为DataFrame对象赋值
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转载自blog.csdn.net/BBJG_001/article/details/104490702
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