Data visualization helps communicate insights and understand trends. Matplotlib and Seaborn are the most widely used Python visualization libraries.
import matplotlib.pyplot as plt
plt.plot(df["year"], df["sales"])
plt.xlabel("Year")
plt.ylabel("Sales")
plt.show()
plt.bar(df["department"], df["salary"])
plt.hist(df["age"], bins=10)
sns.boxplot(x=df["salary"])
sns.heatmap(df.corr(), annot=True, cmap="coolwarm")
plt.scatter(df["height"], df["weight"])
sns.pairplot(df)
Data visualization is essential for EDA and communicating findings. Matplotlib is great for basic plots, while Seaborn offers advanced visualizations.
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