How to create a lag plot for timeseries data?
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# How to create a lag plot for timeseries data?

This recipe helps you create a lag plot for timeseries data

0

## Recipe Objective

Lag plots are most commonly used to look for patterns in time series data.

So this recipe is a short example on How to create a lag plot for timeseries data. Let's get started.

## Step 1 - Import the library

``` import pandas as pd ```

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays.

## Step 2 - Setup the Data

``` df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/a10.csv', parse_dates=['date']).set_index('date') ```

Here we have imported random time series dataset from github.

## Step 3 - Plotting Lag plot

``` pd.plotting.lag_plot(df, lag=1) ```

Using lag_plot, we are plotting our dataset. Lag here is set to be 1.

## Step 4 - Let's look at our dataset now

Once we run the above code snippet, we will see:

```Scroll down to the ipython file to look at the results.
```

This dataset has almost all the featurers of time variation. Lag clearly helps in understanding how these features are set in.

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