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1PRIDE

Your first chart

Level 1 · Lesson 6

Hook

Numbers are how you find the story. Charts are how you tell it. Your first chart doesn’t need to be pretty — it needs a title, axis labels, and a data source.

Concept

matplotlib’s basic chart loop:

  1. Pull the data into a DataFrame.
  2. Pick the right chart type. Comparing values across categories → bar chart.
  3. Plot. df.plot(kind='bar', x='label', y='value').
  4. Add title, axis labels, and a source caption. Always.
  5. Save or plt.show().
import matplotlib.pyplot as plt
import pandas as pd
from sqlalchemy import create_engine


eng = create_engine("postgresql+psycopg://onepride:lions@localhost:5432/onepride")


df = pd.read_sql(
    """SELECT player_display_name, SUM(rushing_yards) AS yards
       FROM weekly_stats
       WHERE recent_team = 'DET' AND season = 2024 AND season_type = 'REG'
       GROUP BY player_display_name
       ORDER BY yards DESC
       LIMIT 5""",
    eng,
)


ax = df.plot(kind='barh', x='player_display_name', y='yards',
             color='#0076B6', legend=False, figsize=(7, 4))
ax.invert_yaxis()                     # top bar = leader
ax.set_title('Lions 2024 rushing leaders (regular season)')
ax.set_xlabel('Rushing yards')
ax.set_ylabel('')
ax.figure.text(0.99, 0.01, 'Source: nflverse', ha='right', fontsize=8, color='gray')
plt.tight_layout()
plt.savefig('rushing-leaders-2024.png', dpi=150)

(GROUP BY is technically Level 2 territory — but you can use the snippet above and read it as “sum per player.” You’ll write your own next level.)

Lions example

The snippet above is the example. Run it in a Jupyter cell and you’ll get a horizontal bar chart with Jahmyr Gibbs on top (≈1,400 rushing yards), David Montgomery second (≈775), then situational backs below.

A few small choices that matter:

  • Horizontal bars (barh) when labels are long names. Vertical bar charts cram or rotate the labels.
  • Invert the y-axis so the leader is on top — that’s the convention readers expect.
  • color='#0076B6' — one color, the 1PRIDE accent. No rainbow per bar.
  • A source caption. Always. Charts get screenshotted out of context.

Try it

Make a bar chart of Lions passing yards by week for 2024 regular season. Use vertical bars (kind='bar'), week on the x-axis, yards on the y-axis. Title, axis labels, source caption — all three.

Common mistakes

  • No title. A chart without a title is a Rorschach test.
  • No source. You can always re-find it, but the reader can’t.
  • Default matplotlib palette. Tab-orange and sky-blue everywhere. Pick a color that matches your subject. Honolulu Blue (#0076B6) for Lions charts.
  • Skipping plt.tight_layout(). Long labels get cut off in the saved PNG.
  • plt.savefig after plt.show(). plt.show() resets the figure in some setups. Save first, then show — or skip show and just save.

Quick check

  1. Why barh instead of bar for player-name bar charts?
  2. What three labels does every chart need?
  3. What does ax.invert_yaxis() do in a horizontal bar chart, and why?