AgpaloLegalAndJudicialEthicspdf

AgpaloLegalAndJudicialEthicspdf



 
 
 
 
 
 
 

AgpaloLegalAndJudicialEthicspdf

AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJudicialEthicspdf
AgpaloLegalAndJud

https://colab.research.google.com/drive/1_y0ZBWTSQDA94pweENq0gP-mdHTFa09b
https://colab.research.google.com/drive/15jOSAn2F62MXoMeGOHAKyzUw3LIYmfHh
https://colab.research.google.com/drive/1dwJvxfTrxLxg6HM9sJ2hgGuXhFqGo7SV
https://colab.research.google.com/drive/1OYp0vurdAomQEaZEn7-YEkwTfZpo_hbR
https://colab.research.google.com/drive/1yAIyrOQ0l8KCQAMhUZ1foJedqOdw4qLk

A:

You could try
import pandas as pd

df = pd.read_csv(“/Users/dulceGarcia/Desktop/pandas_examples/tag_count_fe2.csv”)

df.drop_duplicates().sort(‘date’, ascending=False).drop_duplicates(subset=’name’).reset_index(drop=True).rename(columns={‘name’:’my_name’})

Output:
date my_name
0 2016-12-01 1
1 2016-12-01 1
2 2016-12-01 2
3 2016-12-02 2
4 2016-12-02 1
5 2016-12-02 2
6 2016-12-03 1
7 2016-12-03 2

For more information about Pandas, I recommend that you read the documentation.
PS: You can also use this very same
a2fa7ad3d0

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