# How to compute the exponential moving average with Pandas using Python

• 1 minExponential moving averages are useful when you want to allocate more weight to more recent observations when you compute your average.

The **DataFrame.ewm() **method can be used to compute the exponential moving average.

The method will require you to pass the decay parameter. (**com**)

Enough talking,

## Here is the code

```
# To work with dataframes
import pandas as pd
# To get the stock prices
import yfinance as yf
# We get the stock prices
df = yf.download("AAPL", start="2021-01-03")
# We compute the "20 days" exponential moving average
df["ema_20"] = df["Adj Close"].ewm(com=20).mean()
# We plot the ewm_20 along with the close price
df[["ema_20", "Close"]].plot(title="20 days exponential moving average on AAPL stock price")
```

## The results

Here you are! You now know how to compute the exponential moving average with Pandas using Python.

# More on financial analysis

If you want to know more about **Financial Analysis in Python** and avoid the headaches... check out the other articles I wrote by clicking just here: