Time Series Graph using Python

A time-series graph is a line plot that displays trends or patterns over a dataset collected over an interval of time. For example, when you visualize a line plot of the daily sales made by a business, you are visualizing a time-series graph. It is one of the most important data visualizations for every data scientist. So if you want to learn how to visualize it using Python, this article is for you. In this article, I will take you through a tutorial on visualizing a time series graph using Python.

Time Series Graph

A time-series graph is a line plot used to visualize time series data. Time-series data is the data collected over an interval of time. Some of the popular examples of time series data are stock price data, daily sales data, daily covid cases data, etc.

While visualizing a time-series graph, the time intervals lie on the x-axis, and the data points collected over those time intervals lie on the y-axis. For example, while visualizing a time-series graph of stock price data, the date column will lie on the x-axis, and the price column will lie on the y-axis.

I hope you now have understood what a time series chart is and why it is used in data science. Now, in the section below, I will walk you through how to visualize a time series graph using Python.

Time Series Graph using Python

To visualize a time series graph using Python, I will be using a stock price dataset. There are many libraries in Python for data visualization; I will be using Plotly as it is easy to visualize interactive visualizations using plotly. So let’s start this task by collecting the latest stock price data of Apple:

import pandas as pd
import yfinance as yf
import datetime
from datetime import date, timedelta
today = date.today()

d1 = today.strftime("%Y-%m-%d")
end_date = d1
d2 = date.today() - timedelta(days=360)
d2 = d2.strftime("%Y-%m-%d")
start_date = d2

data = yf.download('AAPL', 
                      start=start_date, 
                      end=end_date, 
                      progress=False)
print(data.head())

                  Open        High  ...   Adj Close     Volume
Date                                ...                       
2021-01-19  127.779999  128.710007  ...  127.046783   90757300
2021-01-20  128.660004  132.490005  ...  131.221054  104319500
2021-01-21  133.800003  139.669998  ...  136.031372  120150900
2021-01-22  136.279999  139.850006  ...  138.217926  114459400
2021-01-25  143.070007  145.089996  ...  142.044327  157611700

[5 rows x 6 columns]

The above data is collected by using the yfinance API. You can know more about it from here. Now below is how you can visualize a time series graph using Python:

import plotly.express as px
figure = px.line(data, x = data.index, y = "Close")
figure.show()

Summary

A time-series graph is a line plot used to visualize time series data. Time-series data is the data collected over an interval of time. While visualizing a time-series graph, the time intervals lie on the x-axis, and the data points collected over those time intervals lie on the y-axis. I hope you liked this article on visualizing a time series chart using Python. Feel free to ask valuable questions in the comments section below.