How do i calculate the percentage increase or decrease in a list of values with python

user_12216066 0
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I want to calculate the percentage change either increase or decrease in a list. here is my list ages = [20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 13.4, 140.9]

here is my code

def percent_change_in_naira(value):
  try:
    for i in value:
        if old_num > new_num:
          ((((old_num-new_num)/old_num)*100))
        elif old_num == new_num:
          0
        else:
          ((((new_num-old_num)/old_num)*100))
    return value
  except ZeroDivisionError:
        return 0

How do assign 'new_num' to a new number on the list above and 'old_num' to a previous number on the list above?

Thanks in advance

python-3.x list function python
4 Answers

In Python (as suggested by @sahasrara62 in the comments)

ages = [20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 13.4, 140.9]

changes = []
for x1, x2 in zip(ages[:-1], ages[1:]):
    try:
        pct = (x2 - x1) * 100 / x1
    except ZeroDivisionError:
        pct = None
    changes.append(pct)

# [50.2463054187192,
#  -33.44262295081967,
#  124.13793103448275,
#  11.208791208791212,
#  -41.699604743083,
#  -54.576271186440685,
#  951.4925373134328]

Using numpy

import numpy as np

ages = np.array([20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 
                 13.4, 140.9])
diff = ages[1:] - ages[:-1]
changes = diff / ages[1:] * 100

# [ 50.24630542 -33.44262295 124.13793103  11.20879121
#  -41.69960474 -54.57627119 951.49253731]

Using Pandas

import pandas as pd

ages = pd.Series([20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 
                  13.4, 140.9])
changes = ages.pct_change() * 100

# 0           NaN
# 1     50.246305
# 2    -33.442623
# 3    124.137931
# 4     11.208791
# 5    -41.699605
# 6    -54.576271
# 7    951.492537
# dtype: float64
user_16095140

You can try this: Will get current and next value by index value of list

def percent_change_in_naira(value):
    output = []
    try:
        for index,i in enumerate(range(len(value))):
            if i == 0:
                output.append(i)
            else:
                old_num = value[index-1]
                new_num = value[index]                    
                output.append(round((((old_num-new_num)/old_num)*100), 3))
    except ZeroDivisionError:
            output.append(0)
    return output

expected output is:

[0, -50.246, 33.443, -124.138, -11.209, 41.7, 54.576, -951.493]
user_56470380

You can use a list comprehension:

i = [20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 13.4, 140.9]

i = [0]+[(i[n+1]-i[n])/i[n]*100 if i[n] else 0 for n in range(len(i)-2)]

print(i)

Output:

[0, 50.2463054187192, -33.44262295081967, 124.13793103448273, 11.208791208791212, -41.69960474308301, -54.576271186440685]
user_135524700

The simplest (and fastest) way calculate running percent changes is with a numpy.array.

import numpy as np
li = np.array([20.3, 30.5, 20.3, 45.5, 50.6, 29.5, 13.4, 140.9])

perc=[0.0]+list(np.round((li[1:]/li[:-1]-1)*100,decimals=1))

print(perc)

Output:

[0.0, 50.2, -33.4, 124.1, 11.2, -41.7, -54.6, 951.5]

Note that if you hit a division by zero, numpy will automatically put 'inf' as a result.

user_135029120
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