根据其他列使用python重新排序（排序）CSV中的行

Question

I am trying to reorder rows in csv where I want to have "All" as the last row, in csv. I have tried using sort_index and sort_Values but I have not been able to achieve what I want. Here is my code:

import pandas as pd
import csv

df1=pd.read_csv("C:\\testfolder\\testdemofinal1.csv",sep=',',na_filter=False)

df=pd.DataFrame(df1)

a=df.pivot_table(index=['Parameter1_Calculation','Parameter2_Calculation'],columns='Measure Names', values='Measure Values',aggfunc='first',dropna=True,margins_name='All')

---

#a=a.sort_values(by='Total Earn',ascending=0)

This does sort the rows but does not give me the right result.

---

#a=a.sort_index(by=['Parameter1_Calculation','Parameter2_Calculation'],ascending=[True,False])

This gives me error.

b=a.to_csv("C:\\newfile1.csv",sep=',')

I have attached the sample csv below:

Thanks in advance

I have a sample of textual data below:

Parameter1   Parameter2 CPS  CallE  Calls ClickEarn      Clicks  
ABC - Health 8/23/2017  0.78    0    0    31.5          15  
Ad Network   8/23/2017  0.01    0    0     1.3           1  
All             All     0.27    0    0    17,502,274    3,493,532
Quotes       8/23/2017  0       0    0      0            0  

Answer 1

The fast but stupid way is to drop that row and append that later.

data = df
c = df[df['Parameter1_Calculation']=='ALL']
data.drop(c.index).append(c)

but this may create unexpected result when you have more than one row