How to find the change between groups in a live data, using python?

Issue

This Content is from Stack Overflow. Question asked by sam_sam

Here is a sample data of a larger race result dataset that I have.

import pandas as pd
  
# initialize data of lists.
data = {'Car': ['A', 'B', 'C', 'D','C', 'A', 'B', 'D','B','C'],
        'time': [2012, 2013, 2000, 2012, 2009, 2012, 2013,2000, 2002, 1999],
        'pos':[2,1,1,1,3,2,2,2,3,1],
        'update':[110738604,110738604,110738604,110738604, 110743097, 110743097, 110743097, 110743097, 110809881, 110509881]}
  
  
# Create DataFrame
df = pd.DataFrame(data)
  
# Print the output.
df

This dataset gets updated every few seconds(not in a fix interval I guess),
I want to find the Top car for every update and return a message that which car is leading, also in the next update if the top car is faster than previous top one then change the top car announcement.

I did

df_sliced={}
for name in df['update'].unique():
    df_sliced[name]=df[df['update']==name]
    df_sliced[name] = df_sliced[name].sort_values('time')
    top = df_sliced[name]['time'].idxmin()
    print('the top car is {} for update {}.'.format(df_sliced[name]['Car'].loc[top], df_sliced[name]['update'].loc[top]))
    

I tried to first add a new column to display word ‘top’ if the second group top be faster than first group,

df_sliced[name]['top'] = df_sliced[name]['time'].loc[[top]].values > df_sliced[name]['time'].min()

yet stoked and don’t know how to do this.Please help.



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