Cumulative Computations On Pandas Series

Overview:

  • Number of participants so far arrived for a meeting, maximum rainfall over the century, the coldest temperature over decades - they all require computing of cumulative results like Cumulative Sum, Cumulative Maximum and Cumulative Minimum.
  • The functions Series.cumsum(), Series.cummax() and Series.cummin() of the pandas.Series class allow performing these cumulative operations on a pandas Series. The two-dimensional collection pandas.DataFrame also supports cumulative operations.

Calculating cumulative sum of a pandas.Series:

  • How many students have arrived so far, what is the current water level in a dam are some of the examples for cumulative sum.
  • As events occur over a period of time, cumulative sum gets incremented or decremented based on the nature of events.
  • When two students enter into the class, they add to the cumulative student count. In the similar way, when the water is released at a rate greater the incoming rate, the water level at the dam recedes.
  • The function Series.cumsum() computes the cumulative sum of the elements present in a pandas Series instance.

 

Example:

# Python example program to compute the cumulative sum of

# a pandas.Series instance

import pandas as pds

 

# Forex inflow and outflow of a central bank in billions of US Dollars

forexReserves           = [430, -20, -145, 500, -440];

forexSeries             = pds.Series(forexReserves);

cumulativeReserves      = forexSeries.cumsum();

 

print("Cumulative forex reserves in billions of US Dollars:");

print(cumulativeReserves);

 

Output:

Cumulative forex reserves in billions of US Dollars:

0    430

1    410

2    265

3    765

4    325

dtype: int64

Calculating cumulative maximum of a pandas.Series:

  • The data structure pandas.Series is designed to store lengthy time series data as well as to perform computations on them.
  • The Series.cummax() finds the cumulative maximum of the elements present in a pandas.Series object.
  • The Python example code calculates the cumulative maximum of a city’s rainfall over a week.

Example:

# Example Python program to find the cumulative maximum

# for the elements present in pandas.Series

import pandas as pds

 

# Rainfall data in inches

rainFall    = [0.04, 0.0, 0.03, 0.17, 0.24];

 

# Create a pandas Series

rainSeries  = pds.Series(rainFall);

 

# Find the cumulative maximum rainfall

cumMaxRain  = rainSeries.cummax();

 

print("Daily rainfall:");

print(rainSeries);

 

print("Cumulative maximum rainfall over the week:");

print(cumMaxRain);

 

Output:

Daily rainfall:

0    0.04

1    0.00

2    0.03

3    0.17

4    0.24

dtype: float64

Cumulative maximum rainfall over the week:

0    0.04

1    0.04

2    0.04

3    0.17

4    0.24

dtype: float64

 

Calculating cumulative minimum of a pandas.series:

  • Series.cummin() function, finds the cumulative minimum for a pandas.Series().
  • The Python example finds the cumulative minimum for a city’s rainfall data over a period of one week.

Example:

# Example Python program to find the cumulative minimum

# for the elements present in pandas.Series

import pandas as pds

 

# Python list containing temperature history of a city for seven days

cityTemp    = [74,75,72,73,71,70];

 

# Create pandas series from the Pythonlist

tempSeries  = pds.Series(cityTemp);

 

# Find the cumulative minimum temperature

cumMinTemp  = tempSeries.cummin();

 

print("Daily temperature:");

print(tempSeries);

 

print("Cumulative minimum temperature over the week:");

print(cumMinTemp);

Output:

Daily temperature:

0    74

1    75

2    72

3    73

4    71

5    70

dtype: int64

Cumulative minimum temperature over the week:

0    74

1    74

2    72

3    72

4    71

5    70

dtype: int64

 

Calculating cumulative product of a pandas.series:

  • Using the Series.cumprod() cumulative product of a pandas.Series can be calculated.

Example:

# Python example program to calculate the cumulative product

# of a pandas.series

import pandas as pds

 

# Create a pandas series

series              = pds.Series([10, 20, 30, 40, 50, 60, 70]);

 

# Compute the cumulative product of the series

cumulativeProduct   = series.cumprod();

print("Contents of the pandas series instance:");

print(series);

 

print("Cumulative product of the series:");

print(cumulativeProduct);

Output:

Contents of the pandas series instance:

0    10

1    20

2    30

3    40

4    50

5    60

6    70

dtype: int64

Cumulative product of the series:

0             10

1            200

2           6000

3         240000

4       12000000

5      720000000

6    50400000000

dtype: int64

 


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