Calculating Exponential Moving Average in Pandas
This tutorial will discuss calculating ewm (exponential moving average) in Pandas.
Steps to calculate exponential moving average in Pandas
Following are the steps to find ewm values in Pandas.
Import Pandas
We need to import pandas to get started.
import pandas as pd
Creating a Pandas DataFrame
Now let us create a sample DataFrame with the column price to calculate ewm.
data = {"prices": [22.27, 22.19, 22.08, 22.17, 22.18]}
df = pd.DataFrame(data)
Let’s take a look at our DataFrame.
print(df)
Output:
prices
0 22.27
1 22.19
2 22.08
3 22.17
4 22.18
Use rolling()the function to partition the DataFrame
We will now use rolling()the roll_data function to roll our DataFrame with a defined span size and split our DataFrame into two DataFrames.
span = 2
sma = df.rolling(window=span, min_periods=span).mean()[:span]
We min_periodspass the window size and the parameter to rolling()the function, which is a predefined variable.
Now let's insert the rest of the DataFrame into a separate DataFrame.
rest = df[span:]
Calculate exponential moving averages using the pd.concat()and functionsewm()
Now that we have successfully partitioned the default DataFrame, we will use the pd.concat()and ewm()functions to calculate the exponential moving averages over the columns of the DataFrame.
ewm1 = pd.concat([sma, rest]).ewm(span=span, adjust=False).mean()
ewm()We calculated the ewm using the function in the above code .
We pass spanthe parameter. Additionally, adjustthe parameter is passed as False to prevent the imbalance of relative weights from being taken into account during initiation.
Now let's print the ewm value to see the output.
print(ewm1)
Output:
prices
0 NaN
1 22.230000
2 22.130000
3 22.156667
4 22.172222
As shown in the above output, we have successfully calculated the ewm value for the sample DataFrame. Hence, we can successfully find the ewm value in Pandas DataFrame.
For reprinting, please send an email to 1244347461@qq.com for approval. After obtaining the author's consent, kindly include the source as a link.
Related Articles
Convert Tensor to NumPy array in Python
Publish Date：2025/05/03 Views：85 Category：Python
-
This tutorial will show you how to convert a Tensor to a NumPy array in Python. Use the function in Python Tensor.numpy() to convert a tensor to a NumPy array Eager Execution of TensorFlow library can be used to convert tensor to NumPy arra
Saving NumPy arrays as images in Python
Publish Date：2025/05/03 Views：193 Category：Python
-
In Python, numpy module is used to manipulate arrays. There are many modules available in Python that allow us to read and store images. An image can be thought of as an array of different pixels stored at specific locations with correspond
Transposing a 1D array in NumPy
Publish Date：2025/05/03 Views：98 Category：Python
-
Arrays and matrices form the core of this Python library. The transpose of these arrays and matrices plays a vital role in certain topics such as machine learning. In NumPy, it is easy to calculate the transpose of an array or a matrix. Tra
Find the first index of an element in a NumPy array
Publish Date：2025/05/03 Views：58 Category：Python
-
In this tutorial, we will discuss how to find the first index of an element in a numpy array. Use where() the function to find the first index of an element in a NumPy array The function in the numpy module where() is used to return an arra
Remove Nan values from NumPy array
Publish Date：2025/05/03 Views：118 Category：Python
-
This article discusses some built-in NumPy functions that you can use to remove nan values. Remove Nan values using logical_not() and methods in NumPy isnan() logical_not() is used to apply logical NOT to the elements of an array. isn
Normalizing a vector in Python
Publish Date：2025/05/03 Views：51 Category：Python
-
A common concept in the field of machine learning is to normalize a vector or dataset before passing it to the algorithm. When we talk about normalizing a vector, we say that its vector magnitude is 1, being a unit vector. In this tutorial,
Calculating Euclidean distance in Python
Publish Date：2025/05/03 Views：128 Category：Python
-
In the world of mathematics, the shortest distance between two points in any dimension is called the Euclidean distance. It is the square root of the sum of the squares of the differences between the two points. In Python, the numpy, scipy
Element-wise division in Python NumPy
Publish Date：2025/05/03 Views：199 Category：Python
-
This tutorial shows you how to perform element-wise division on NumPy arrays in Python. NumPy Element-Wise Division using numpy.divide() the function If we have two arrays and want to divide each element of the first array with each element
Convert 3D array to 2D array in Python
Publish Date：2025/05/03 Views：79 Category：Python
-
In this tutorial, we will discuss the methods to convert 3D array to 2D array in Python. numpy.reshape() Convert 3D array to 2D array using function in Python [ numpy.reshape() Function](numpy.reshape - NumPy v1.20 manual)Changes the shape
