Chart styling with matplotlib

afp-chart-style.py

import pandas as pd
import matplotlib.pyplot as plt

csv = pd.read_csv('https://raw.githubusercontent.com/corintxt/AFP_data/refs/heads/main/data/US_VEP_Turnout_Rates_v1.1.csv')

df = csv[['YEAR','TURNOUT_RATE_PRES']] \
        .dropna()\
        .query('YEAR >= 1900')

### DRAW THE CHART
# Font settings
plt.rcParams.update(
                {'font.family': 'Source Sans Pro',
                "svg.fonttype": 'none'
                })

# Define plot size
plt.figure(figsize=(6, 4))

## Plot the data
plt.plot(df['YEAR'],
         df['TURNOUT_RATE_PRES'],
          linewidth=2)

## Set title and subtitle
plt.suptitle("US election turnout",
             x=0.1,
             y=1.02,
             fontsize=20, 
             fontweight='bold',
             ha='left')
plt.title("Voter turnout in the 2024 election was still among the highest since 1900",
          x= -.03,
          pad=15,
          fontsize=10,
          fontweight='semibold',
          ha='left',
          )
# Add source credit
plt.figtext(0.1, 0.01, 
            "Source: UF Election Lab", 
            ha="left", 
            fontsize=8)

### FORMAT THE CHART
# Remove frame
ax = plt.gca()
ax.set_frame_on(False)

# Control Y start and end point
ax.set_ylim([0.44, 0.75])

# Change decimal to percentage
ticks = ax.get_yticks()
ax.set_yticklabels(['{:,.0%}'.format(x) for x in ticks])

# Define custom grid marks
ax.grid(axis="y", 
        color="grey", 
        alpha=.5, 
        linewidth=.5, 
        linestyle="--")

# Customize x-ticks
plt.tick_params(axis='x', length=5, direction='out')
plt.tick_params(axis='y', left=False)

# Save svg
plt.savefig('election-turnout-afp.svg',bbox_inches='tight')