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Top Five Pandas Functions for Data Scientists (And How to Use Them)

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Hey everyone. Quick video on what I think are the top five most useful pandas library methods for data analysis. Mastering these will take you a long way in your projects.

5. Import / Output Methods
4. Data Selection
3. Boolean Selections
2. Concat
1. GroupBy

Let me know what I left out!

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Full code from the video:
import pandas as pd

excel_file = 'Docs/contacts1.xlsx'
df = pd.read_excel(excel_file)
print(df)

print(df.loc[:,'Name'])
print(df.iloc[:,0])

print(df[df['Title'] =='Engineer'])

excel_file_2 = 'Docs/contacts2.xlsx'
df2 = pd.read_excel(excel_file_2)

df3 = pd.concat([df, df2], axis=0)
print(df3)

total_count = df3.groupby(['Title']).count()
print(total_count['Name'])

github.com/Derrick-Sherrill/DerrickSherrill.com/bl…
Packages (& Versions) used in this video:
Python==3.7
Pandas==0.25.0

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Code from this tutorial and all my others can be found on my GitHub:
github.com/Derrick-Sherrill/DerrickSherrill.com

Check out my website:
www.derricksherrill.com/

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