Extracting statistics from time series data

One of the main reasons that we want to analyze time series data is to extract interesting statistics from it. This provides a lot of information regarding the nature of the data. In this recipe, we will take a look at how to extract these stats.

How to do it…

1. Create a new Python file, and import the following packages:

   import numpy as np
   import pandas as pd
   import matplotlib.pyplot as plt
   
   from convert_to_timeseries import convert_data_to_timeseries

2. We will use the same text file that we used in the previous recipes for analysis:

   # Input file containing data
   input_file = 'data_timeseries.txt'

3. Load both the data columns (third and fourth columns):

   # Load data
   data1 = convert_data_to_timeseries(input_file, 2)
   data2 = convert_data_to_timeseries(input_file, 3)

4. Create a pandas data structure to hold this data. This dataframe is like a dictionary that has keys and values:

   dataframe = pd.DataFrame({'first': data1, 'second': data2})

5. Let's start extracting some...