如何将数据框中的每一行乘以csv文件中的值答案

【问题标题】：How to multiply every row in dataframe by value from csv file如何将数据框中的每一行乘以csv文件中的值
【发布时间】：2021-06-15 21:32:11
【问题描述】：

这是我的 csv 文件 CSV

我试图取“最小角度”和“最大角度”列的平均值，然后将结果数据框中的每一行与单元格 D8 中的“角度转换因子”相乘。同样，我想对“Torque Min”和“Torque Max”做同样的事情（获取平均值，然后将结果数据帧乘以单元格 E8 中的“Torque Conversion Factor”）。

到目前为止，这是我的代码：

import matplotlib.pyplot as plt                 
from matplotlib.pyplot import show, plot                                            
import numpy as np
from scipy.signal import savgol_filter
import os


def Torque_Analysis(filename):

    #Importing CSV Data and Defining 'AngleDF' and 'TorqueDF'

    Angle_Data = ['Angle Min' , 'Angle Max']                                                                
    Torque_Data = ['Torque Min' , 'Torque Max']
    AngleCol = ['Angle Conversion Factor']
    TorqueCol = ['Torque Conversion Factor']

    AngleConvFactor = pd.read_csv(filename, skiprows=6, usecols = AngleCol, nrows = 1, engine='python')
    TorqueConvFactor = pd.read_csv(filename, skiprows=6, usecols = TorqueCol, nrows = 1, engine='python')

    AngleDF = pd.read_csv(filename, skiprows=17,usecols=Angle_Data, skipfooter=4, engine='python')
    TorqueDF = pd.read_csv(filename, skiprows=17,usecols=Torque_Data, skipfooter=4, engine='python')

    #Calculating the average of 'Angle Min', 'Angle Max'

    col = AngleDF.loc[: ,'Angle Min':'Angle Max']                                                           
    AngleDF['Angle Mean'] = col.mean(axis=1)
    AngleDFmean= AngleDF['Angle Mean']

    #Calculating the average of 'Torque Min', 'Torque Max'

    col = TorqueDF.loc[: ,'Torque Min':'Torque Max']            
    TorqueDF['Torque Mean'] = col.mean(axis=1)
    TorqueDFmean= TorqueDF['Torque Mean']

    #Multiplying Torque Mean values by Torque conversion factor

    TorqueDFmean[:] = TorqueConvFactor * TorqueDFmean

    #Multiplying Angle Mean values by Angle conversion factor

    AngleDFmean[:] = AngleConvFactor * AngleDFmean

我不断收到错误

“ValueError：无法使用长度与值不同的切片索引器进行设置”。

【问题讨论】：

标签： python pandas dataframe multiplication scalar

【解决方案1】：

您的 AngleConcFactor 和 TorqueConvFactor 在您的代码中仍然是 1x1 数据帧。只需稍微清理一下您的功能，就可以满足您的需求：

def Torque_Analysis(filename):
    Angle_Data = ['Angle Min' , 'Angle Max']                                                                
    Torque_Data = ['Torque Min' , 'Torque Max']
    AngleCol = ['Angle Conversion Factor']
    TorqueCol = ['Torque Conversion Factor']

    AngleConvFactor = pd.read_csv(filename, skiprows=6, usecols=AngleCol, nrows=1, engine='python').iat[0,0]
    TorqueConvFactor = pd.read_csv(filename, skiprows=6, usecols=TorqueCol, nrows=1, engine='python').iat[0,0]

    AngleDF = pd.read_csv(filename, skiprows=17, usecols=Angle_Data, skipfooter=4, engine='python')
    TorqueDF = pd.read_csv(filename, skiprows=17, usecols=Torque_Data, skipfooter=4, engine='python')

    AngleDF["Angle Mean"] = AngleDF[["Angle Min", "Angle Max"]].mean(axis=1)*AngleConvFactor
    TorqueDF["Torque Mean"] = TorqueDF[['Torque Min', "Torque Max"]].mean(axis=1)*TorqueConvFactor

请注意，我已使用 .iat[0,0] 将您的 1x1 DataFrame 转换为标量值。

【讨论】：