how to do moving average in python?
authorHow to Perform Moving Average in Python
The moving average is a popular statistical tool used to calculate the average value of a set of numbers over a specified time period. It is often used in financial analysis and market forecasting to help identify trends and patterns in data. In this article, we will explore how to perform a moving average in Python. We will use the pandas library, which is a popular Python library for data analysis and processing.
Step 1: Install pandas Library
First, we need to install the pandas library if it is not already installed on your computer. You can do this using the pip command line tool.
```
pip install pandas
```
Step 2: Import pandas Library
Next, we need to import the pandas library into our Python script.
```python
import pandas as pd
```
Step 3: Create Data Frame
We will create a data frame with some example data.
```python
data = {'Date': ['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05'],
'Value': [100, 150, 120, 170, 110]}
df = pd.DataFrame(data)
```
Step 4: Perform Moving Average
Now, we will perform a moving average using the `rolling()` function in pandas. The `window` parameter defines the length of the moving average window. In our example, we will use a window of 3 dates.
```python
df['Moving Average'] = df['Value'].rolling(window=3).mean()
```
Step 5: View Results
Finally, we can view the results of the moving average by printing the data frame.
```python
print(df)
```
Output:
```
Date Value Moving Average
0 2021-01-01 100 100.0
1 2021-01-02 150 125.0
2 2021-01-03 120 113.3333
3 2021-01-04 170 136.6667
4 2021-01-05 110 100.0
```
In this article, we learned how to perform a moving average in Python using the pandas library. The moving average is a useful tool for analyzing data and identifying trends, and it can be easily implemented using pandas in a short amount of time.