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Data Analysis with Pandas and Python

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Data - Multiple Worksheets.xlsx
Data - Multiple Worksheets.xlsx
 
 
Data - Single Worksheet.xlsx
Data - Single Worksheet.xlsx
 
 
DataFrames 1.ipynb
DataFrames 1.ipynb
 
 
DataFrames 2.ipynb
DataFrames 2.ipynb
 
 
DataFrames 3.ipynb
DataFrames 3.ipynb
 
 
Groupby object.ipynb
Groupby object.ipynb
 
 
Input and Output in pandas.ipynb
Input and Output in pandas.ipynb
 
 
Intro to Jupyter Notebook.ipynb
Intro to Jupyter Notebook.ipynb
 
 
Merging, Joining, and Concatenating DataFrames.ipynb
Merging, Joining, and Concatenating DataFrames.ipynb
 
 
Multi Index.ipynb
Multi Index.ipynb
 
 
Options and Settings.ipynb
Options and Settings.ipynb
 
 
Python Crash Course.ipynb
Python Crash Course.ipynb
 
 
README.md
README.md
 
 
Restaurant - Customers.csv
Restaurant - Customers.csv
 
 
Restaurant - Foods.csv
Restaurant - Foods.csv
 
 
Restaurant - Week 1 Sales.csv
Restaurant - Week 1 Sales.csv
 
 
Restaurant - Week 1 Satisfaction.csv
Restaurant - Week 1 Satisfaction.csv
 
 
Restaurant - Week 2 Sales.csv
Restaurant - Week 2 Sales.csv
 
 
Series.ipynb
Series.ipynb
 
 
Test.ipynb
Test.ipynb
 
 
Viuslization.ipynb
Viuslization.ipynb
 
 
Working with Dates and Times.ipynb
Working with Dates and Times.ipynb
 
 
Working with Text Data.ipynb
Working with Text Data.ipynb
 
 
baby_names.xlsx
baby_names.xlsx
 
 
bigmac.csv
bigmac.csv
 
 
chicago.csv
chicago.csv
 
 
ecommerce.csv
ecommerce.csv
 
 
employees.csv
employees.csv
 
 
foods.csv
foods.csv
 
 
fortune1000.csv
fortune1000.csv
 
 
google_stock_price.csv
google_stock_price.csv
 
 
jamesbond.csv
jamesbond.csv
 
 
nba.csv
nba.csv
 
 
new_baby_names.csv
new_baby_names.csv
 
 
new_baby_names_no_index.csv
new_baby_names_no_index.csv
 
 
new_baby_names_no_index_sel_col.csv
new_baby_names_no_index_sel_col.csv
 
 
pokemon.csv
pokemon.csv
 
 
quarters.csv
quarters.csv
 
 
revenue.csv
revenue.csv
 
 
salesmen.csv
salesmen.csv
 
 
worldstats.csv
worldstats.csv
 
 

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Data Analysis with Pandas and Python

Codes include:

  1. sorting
  2. filtering
  3. aggregating
  4. de-duplicating
  5. pivoting
  6. manipulating
  7. deleting
  8. merging
  9. visualizing

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Data Analysis with Pandas and Python

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