This tutorial will guide you through the basics of creating charts using Plotly, a powerful Python library for interactive visualizations.

Introduction

Plotly is a graphing library for Python that makes interactive, publication-quality graphs online. It is particularly useful for creating interactive charts and dashboards.

Getting Started

Before you start, make sure you have Plotly installed. You can install it using pip:

pip install plotly

Creating a Simple Line Chart

Let's create a simple line chart. A line chart is a type of chart that displays data points connected by straight line segments.

import plotly.express as px

df = px.data.tips()
fig = px.line(df, x='time', y='total_bill', title="Total Bill Over Time")
fig.show()

Line Chart Example

In the example above, we used the tips dataset provided by Plotly. The time column is on the x-axis, and the total_bill column is on the y-axis.

Creating a Bar Chart

A bar chart is a type of chart that uses rectangular bars to represent data. The bars can represent the values of different categories.

fig = px.bar(df, x='day', y='total_bill', title="Total Bill by Day")
fig.show()

Bar Chart Example

In this example, we used the day column for the x-axis and the total_bill column for the y-axis.

Creating a Scatter Plot

A scatter plot is a type of chart that shows the relationship between two variables.

fig = px.scatter(df, x='total_bill', y='tip', title="Total Bill vs Tip")
fig.show()

Scatter Plot Example

Here, the total_bill column is on the x-axis, and the tip column is on the y-axis.

Learn More

For more information on Plotly and its various chart types, visit the Plotly website.

Happy charting! 📈