STEAM Maker Crafts and Robot Building in Bundang, Seoul

1. Why Customize

Default plots work for exploration. Client reports need controlled ticks, rotated labels, clear legends, and high-DPI exports.

2. Three Pillars

• Ticks — explicit axis intervals (e.g. range(0, 11, 2))
• Label rotation — angle long categories or dense numbers (30° / 45°)
• Legend placement — e.g. loc="upper right" so the box does not cover data

3. Sine Wave + 300 DPI Export

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 10, 50)
y = np.sin(x)

fig, ax = plt.subplots(figsize=(6, 4))
ax.plot(x, y, label="sin(x)", color="blue", linewidth=2)
ax.set_xticks(range(0, 11, 2))
ax.tick_params(axis="x", labelrotation=30)
ax.legend(loc="upper right")
ax.set_title("Customized Sine Wave Plot")
plt.tight_layout()
fig.savefig("sin_plot.png", dpi=300)
plt.show()

dpi=300 produces print-ready sharpness; screens often show ~72–100 DPI.

4. Payment Methods Bar Chart

import pandas as pd

df = pd.read_csv("ecommerce_orders.csv")
payment_counts = df["Payment Method"].value_counts()

fig, ax = plt.subplots(figsize=(7, 5))
ax.bar(
    payment_counts.index,
    payment_counts.values,
    color=["royalblue", "darkorange", "forestgreen"]
)
ax.tick_params(axis="x", labelrotation=45)
ax.set_title("Order Distribution by Payment Method")
ax.set_xlabel("Payment Method")
ax.set_ylabel("Number of Orders")
plt.tight_layout()
fig.savefig("payment_methods_bar.png", dpi=300)
plt.show()

45° rotation keeps long labels like "Cash on Delivery" readable.

5. Method Summary

Task	API	Benefit
Tick intervals	ax.set_xticks(range(...))	Explicit scale
Rotate labels	ax.tick_params(axis="x", labelrotation=angle)	Avoid overlap
Legend location	ax.legend(loc="upper right")	Clear of data
Export	fig.savefig(..., dpi=300)	Sharp print files