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Summary Python Data Operations 2: Methods
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  • Course
  • Programming
  • Institution
  • IE University
  • Book
  • Python Crash Course

Notes of Pandas data operations covered in the Principles of Programming course, part of the Computer Science and AI bachelor degree. The notes are initially written in Jupyter Notebook. They contain practical examples of data operations in python and images to explain the structures and processes....

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  • No
  • Pandas data operations
  • December 9, 2022
  • 11
  • 2022/2023
  • Summary

Subjects

  • python
  • methods
  • arithmatic operations
  • programming
  • reference
  • guide
  • comparison
  • operators
  • commands
  • data analytics
  • data science
  • sql
  • pandas
  • jupyter notebook
  • data operations
  • data frame
  • summary
  • study guide
  • ar

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  • Computer Science
  • Programming
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Python Data Operations 2: Methods
(Using the numpy and pandas packages imported in section one.)

This second section contains:

Arithmetic operations

add
subtract
multiply
divide
Store solution in new column
Comparison

equal to
not equal to
greater than
less than
Other math functions

sum
maximum and minimum
median and mean
standard deviation and variability
Delete rows and columns
Renaming rows and columns
Replacing multiple values
Sort

sort by values
sort by index



pd.set_option('display.max_columns', None)



Arithmetic operation

# create test dataframe
test_df = pd.DataFrame([
['A3', 0, -1, 0, 'si'],
['B1', 1, None, 0, 'no'],
['B3', 4, None, 0, 'no'],
['B3', 5, 1, 0, 'si'],
['A1', 4, 0, None, None],

, ['A3', 1, 2, 1, 'si'],
['C2', 4, 1, 1, 'no']],
columns=['A', 'B', 'C', 'D', 'E'],
index=[f'R{i}' for i in range(7)]
)
test_df


A B C D E

R0 A3 0 -1.0 0.0 si

R1 B1 1 NaN 0.0 no

R2 B3 4 NaN 0.0 no

R3 B3 5 1.0 0.0 si

R4 A1 4 0.0 NaN None

R5 A3 1 2.0 1.0 si

R6 C2 4 1.0 1.0 no



#add 10 to column D
test_df['D'] + 10

R0 10.0
R1 10.0
R2 10.0
R3 10.0
R4 NaN
R5 11.0
R6 11.0
Name: D, dtype: float64


# subtracting a value from column D
test_df['D'] - 10
test_df['D'].sub(10)

R0 -10.0
R1 -10.0
R2 -10.0
R3 -10.0
R4 NaN
R5 -9.0
R6 -9.0
Name: D, dtype: float64


#the above operations will not update the dataframe
test_df

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