Easy method to subtract all the columns from one reference column .Sum and square it and store it

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Whether to compare by the index (0 or ‘index’) or columns (1 or ‘columns’), For Series input, axis to match Series index on

Example_snippet/controller/utility/_method.js/ >>> df = pd.DataFrame({'angles. . .
>>> df = pd.DataFrame({
         'angles': [0, 3, 4],
         ...'degrees': [360, 180, 360]
      ...index = ['circle', 'triangle', 'rectangle']) >>>
angles degrees
circle 0 360
triangle 3 180
rectangle 4 360
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As you may remember from a math course, subtracting a negative number is the same as adding it, So, make all the numbers you want to subtract negative (for this, simply type a minus sign before a number), and then use the SUM function to add up the negative numbers:,As an example, let's subtract numbers in column C from the numbers in column B, beginning with row 2:,Select a range of empty cells that has the same number of rows and columns as your matrices

Example_snippet/controller/utility/_method.js/ =100-10. . .
= 100 - 10
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Once you learned how to subtract cells with a formula, subtracting columns is a breeze, The easiest way to do so is to drag the fill handle from the cell you’ve applied the formula down to the last row of that column

Example_snippet/controller/utility/_method.js/ [cell reference]-TIME(N hours,. . .
[cell reference] - TIME(N hours, 0, 0).
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I need to easy method to do this, Maybe a small function

Example_snippet/controller/utility/_column.js/ import pandas as pd import mat. . .
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

df = pd.read_csv('F:\\Python\\projects\\testdrivingcycles.csv', usecols = ['position', 'ReferenceSpeed', 'speed1', 'speed2', 'speed3', 'speed4', 'speed5', 'speed6', 'speed7', 'speed8', 'speed9', 'speed10'])

dict1 = np.square(df.loc[: , 'ReferenceSpeed': ].subtract(df.ReferenceSpeed, axis = 0).sum()).to_dict()


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