NumPy | Python Methods and Functions

0 NaN 1 0.400000 2 0.000000 3 0.428571 4 0.250000 5 -0.500000 6 0.040000 7 -1.000000 8 inf dtype: float64

First, the n (n = period) values are always * NaN * because there is no previous value to calculate the change.

Syntax:Series.pct_change(periods=1, fill_method = `pad`, limit = None)

Parameters:

periods:Defines gap between current and previous value. Default is 1

fill_method:Defines method used to handle null values

limit:Number of consecutive NaN values to fill before stopping.

Return type:Numeric series with percentage change

** Example # 1: **

In this method A series is created from a Python list using Pandas ` Series () `

. The series does not contain a null value, so ` pct_change () `

is called directly with a default value for the * period * parameter of 1.

` ` |

** Exit:**

0 NaN 1 0.400000 2 0.428571 3 0.250000 4 -0.5000 00 5 0.040000 6 -1.000000 7 inf dtype: float64

As shown in the output, the first n values are always NaN. The remaining values are equal to the percentage change in the old values and are stored in the same position as a number of callers.

** Note. ** Since the second last value was 0, the percentage change is inf. Inf means infinity.

Using the formula, pct_change = x-0/0 = Infinte

** Example # 2: ** Handling null values

In this example, some null values are also created using Numpy`s np.nan method and passed to a list. & # 39; * bfill * & # 39; passed to ` fill_method `

. * bfill * stands for Back fill and will fill zero values with values in their next position.

` ` |

** Exit:**

As you can see from the output, the value at position 1 is 40 because the NaN has been replaced by 14. Therefore, (14-10 / 10) * 100 = 40. The next value is 0 because the percentage change in 14 and 14 is 0,

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