Skip to content

Latest commit

 

History

History
65 lines (49 loc) · 2.83 KB

Project-4.md

File metadata and controls

65 lines (49 loc) · 2.83 KB
Raw

🎨 Project 4 - Using Matplotlib to create a plot in Streamlit

What are we building?

Let's now use Matplotlib to create a plot in a Streamlit app.

How the code works?

Here's an explanation of the code in a step-by-step manner:

  1. Import the matplotlib.pyplot as plt (so that we can later refer to matplotlib.pyplot literally as plt instead of having to type the full version of matplotlib.pyplot. New line of code: Likewise, we import the Streamlit library using import streamlit as st.
  2. Write out the title of the app via st.title().
  3. Create years and population variables that will be used for subsequent steps in creating the plot.
  4. Define fig and ax via fig, ax = plt.subplots(), which will be used in ax.plot() and ax.scatter as well as st.pyplot(fig).
  5. Create the plot via ax.plot() and specifying years and population as input arguments. This will create a line plot.
  6. The line is changed to red dashed line via the third argument r--.
  7. Data points are added via the ax.scatter function.
  8. A second green line with green translucent data points are also added here.
  9. Add labels to the plot as well as the X and Y axes.
  10. Finally, we're going to display the plot via st.pyplot(fig) (recall the fig variable that we defined earlier).

Code

import streamlit as st
import matplotlib.pyplot as plt

st.title('📈 Line plot with Matplotlib')

# Data
years = [1950, 1960, 1970, 1980, 1990, 2000, 2010, 2020]
population = [2.5, 3.0, 3.7, 4.5, 5.3, 6.1, 6.9, 7.7]
population2 = [7.7, 8.1, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0]

# Create plot
# Here we define fig and ax and subsequently replace plt by ax for the plots
fig, ax = plt.subplots()

ax.plot(years, population, 'r--')
ax.scatter(years, population, c='r', alpha=0.6)

ax.plot(years, population2, 'g')
ax.scatter(years, population2, c='g', alpha=0.6)

# Add labels
plt.title('Population Growth')
plt.xlabel('Year')
plt.ylabel('Population (millions)')

# Show plot
# Instead of plt.show() we're using st.pyplot
st.pyplot(fig)

Completed app

The above code gives us the following Streamlit app (GitHub repo | Demo app)

Homework

Now that you have this Matplotlib app completed, can you build upon this Streamlit app by adding input widgets for allowing users to choose a line color or data point color of their choice. After selection, the app will update and generate the corresponding plot with the specified colors.

📣 Learn in Public:

Share your solution (the updated Streamlit app) on social media (Twitter and/or LinkedIn) and tag us (@streamlit).