Python Tutorial (17): Visualisasi Data dengan Matplotlib

pip install matplotlib

import matplotlib.pyplot as plt
import numpy as np
 
# Inline di Jupyter notebook
# %matplotlib inline
 
# Style (opsional)
plt.style.use("seaborn-v0_8-whitegrid")

import matplotlib.pyplot as plt
import numpy as np
 
x = np.linspace(0, 10, 100)
y = np.sin(x)
 
plt.figure(figsize=(10, 5))
plt.plot(x, y, label="sin(x)", color="blue", linewidth=2)
plt.plot(x, np.cos(x), label="cos(x)", color="red", linestyle="--")
 
plt.title("Fungsi Trigonometri")
plt.xlabel("x")
plt.ylabel("y")
plt.legend()
plt.grid(True, alpha=0.3)
plt.tight_layout()
plt.savefig("trig_plot.png", dpi=150)
plt.show()

import matplotlib.pyplot as plt
 
categories = ["Python", "JavaScript", "Java", "Go", "Rust"]
popularity = [29.5, 22.5, 17.8, 8.2, 3.5]
 
plt.figure(figsize=(8, 5))
bars = plt.bar(categories, popularity, color="steelblue", edgecolor="black")
 
for bar, val in zip(bars, popularity):
    plt.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.3,
             f"{val}%", ha="center", fontsize=10)
 
plt.title("Popularitas Bahasa Pemrograman 2026")
plt.ylabel("Persentase (%)")
plt.tight_layout()
plt.show()

import matplotlib.pyplot as plt
 
labels = ["Jakarta", "Surabaya", "Bandung", "Medan"]
values = [45, 28, 22, 15]
 
plt.barh(labels, values, color="coral")
plt.xlabel("Populasi (juta)")
plt.title("Populasi Kota Besar")
plt.show()

import matplotlib.pyplot as plt
import numpy as np
 
np.random.seed(42)
n = 100
x = np.random.randn(n)
y = 2 * x + np.random.randn(n) * 0.5
colors = np.random.rand(n)
sizes = np.random.randint(20, 200, n)
 
plt.figure(figsize=(8, 6))
plt.scatter(x, y, c=colors, s=sizes, alpha=0.6, cmap="viridis")
plt.colorbar(label="Color value")
plt.xlabel("Feature X")
plt.ylabel("Feature Y")
plt.title("Scatter Plot dengan Color & Size")
plt.show()

import matplotlib.pyplot as plt
import numpy as np
 
data = np.random.normal(loc=50, scale=15, size=1000)
 
plt.figure(figsize=(8, 5))
plt.hist(data, bins=30, color="skyblue", edgecolor="black", alpha=0.7)
plt.axvline(data.mean(), color="red", linestyle="--", label=f"Mean: {data.mean():.1f}")
plt.xlabel("Value")
plt.ylabel("Frequency")
plt.title("Distribusi Normal")
plt.legend()
plt.show()

import matplotlib.pyplot as plt
 
labels = ["Desktop", "Mobile", "Tablet"]
sizes = [45, 48, 7]
explode = (0, 0.05, 0)
colors = ["#ff9999", "#66b3ff", "#99ff99"]
 
plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct="%1.1f%%", shadow=True, startangle=90)
plt.title("Traffic by Device")
plt.axis("equal")
plt.show()

import matplotlib.pyplot as plt
import numpy as np
 
fig, axes = plt.subplots(2, 2, figsize=(12, 8))
 
x = np.linspace(0, 10, 50)
 
axes[0, 0].plot(x, np.sin(x))
axes[0, 0].set_title("Sin")
 
axes[0, 1].plot(x, np.cos(x), color="orange")
axes[0, 1].set_title("Cos")
 
axes[1, 0].bar(["A", "B", "C"], [3, 7, 5])
axes[1, 0].set_title("Bar")
 
axes[1, 1].scatter(np.random.rand(30), np.random.rand(30))
axes[1, 1].set_title("Scatter")
 
plt.suptitle("Dashboard 2×2", fontsize=14)
plt.tight_layout()
plt.show()

import pandas as pd
import matplotlib.pyplot as plt
 
df = pd.DataFrame({
    "month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
    "revenue": [120, 135, 148, 142, 160, 175],
    "cost": [80, 85, 90, 88, 95, 100],
})
 
# Line plot langsung dari DataFrame
df.plot(x="month", y=["revenue", "cost"], figsize=(10, 5), marker="o")
plt.title("Revenue vs Cost 2026")
plt.ylabel("Juta Rupiah")
plt.grid(True, alpha=0.3)
plt.show()
 
# Bar chart
df.plot.bar(x="month", y="revenue", figsize=(8, 5), color="steelblue")
plt.title("Revenue per Bulan")
plt.show()
 
# Histogram dari kolom
df["revenue"].plot.hist(bins=5, figsize=(8, 5))
plt.show()

import matplotlib.pyplot as plt
 
fig, ax = plt.subplots(figsize=(10, 6))
 
ax.plot([1, 2, 3, 4], [1, 4, 2, 3], marker="o", markersize=8)
 
ax.set_title("Custom Chart", fontsize=16, fontweight="bold")
ax.set_xlabel("X Axis", fontsize=12)
ax.set_ylabel("Y Axis", fontsize=12)
ax.set_xlim(0, 5)
ax.set_ylim(0, 5)
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.annotate("Peak", xy=(2, 4), xytext=(2.5, 4.5),
            arrowprops=dict(arrowstyle="->", color="red"))
 
plt.tight_layout()
plt.show()

import matplotlib.pyplot as plt
import numpy as np
 
fig, ax = plt.subplots(1, 1, figsize=(10, 5))
ax.plot(np.arange(10), np.arange(10) ** 2)
ax.set_title("OO Style")
fig.savefig("chart.png", bbox_inches="tight", dpi=150)
plt.close(fig)   # penting di script/server untuk free memory