Data Visualization – Plotting Temperatures

Data visualization is an important aspect of data analysis as it allows us to understand complex data sets by presenting them in a visual format. In this article, we will discuss how to plot temperature data using Python’s matplotlib library. We will begin by discussing the data set we will be working with, then move on to the steps required to create the visualization.

Data Set:

The data set we will be using is a collection of temperature readings for a particular location over the course of a year. The data is in CSV format and contains two columns: date and temperature. The date column contains the date of the temperature reading, while the temperature column contains the temperature in degrees Celsius.

Steps:

Step 1: Importing the Libraries

To begin, we need to import the required libraries. We will be using the pandas library to read in the data, and the matplotlib library to create the visualization. We can import the libraries using the following code:

Step 2: Reading in the Data

Next, we need to read in the data using the pandas library. We can do this using the read_csv() function. We will read in the data and store it in a pandas DataFrame:

Step 3: Cleaning the Data

Before we can create the visualization, we need to clean the data. This involves removing any missing values and converting the temperature column to Fahrenheit. We can do this using the following code:

Step 4: Creating the Visualization

Now that the data is cleaned, we can create the visualization. We will be creating a line plot of the temperature over time. We can do this using the following code:

Conclusion

In this article, we have discussed how to plot temperature data using Python’s matplotlib library. We began by discussing the data set we will be working with, then moved on to the steps required to create the visualization. By following these steps, we can create an informative and visually appealing plot of the temperature over time.