pandas 使用熊猫创建矩阵结构
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create matrix structure using pandas
提问by dataviz
I have loaded the below CSV file containing code and coefficient data into the below dataframe df:
我已将包含代码和系数数据的以下 CSV 文件加载到以下数据框 df 中：
CODE|COEFFICIENT
A|0.5
B|0.4
C|0.3
import pandas as pd
import numpy as np
df= pd.read_csv('cod_coeff.csv', delimiter='|', encoding="utf-8-sig")
giving
给予
ITEM COEFFICIENT
0 A 0.5
1 B 0.4
2 C 0.3
From the above dataframe, I need to create a final dataframe as below which has a matrix structure with the product of the coefficients:
从上面的数据帧中，我需要创建一个最终的数据帧，如下所示，它具有矩阵结构和系数的乘积：
A B C
A 0.25 0.2 0.15
B 0.2 0.16 0.12
C 0.15 0.12 0.09
I am using np.multiplybut I am not successful in producing the result.
我正在使用np.multiply但我没有成功产生结果。
采纳答案by piRSquared
numpy as a faster alternative
numpy 作为更快的选择
pd.DataFrame(np.outer(df, df), df.index, df.index)
Timing
定时
Given sample
给定样本
30,000 rows
30,000 行
df = pd.concat([df for _ in range(10000)], ignore_index=True)
回答by Boud
You want to do the math between a vector and its tranposition. Transpose with .Tand apply the matrix dotfunction between the two dataframes.
您想在向量与其换位之间进行数学运算。在两个数据帧之间转置.T并应用矩阵dot函数。
df = df.set_index('CODE')
df.T
Out[10]:
CODE A B C
COEFFICIENT 0.5 0.4 0.3
df.dot(df.T)
Out[11]:
CODE A B C
CODE
A 0.25 0.20 0.15
B 0.20 0.16 0.12
C 0.15 0.12 0.09
