Exploratory Data Analysis (EDA) is the process of examining datasets to summarize their main characteristics, identify patterns, spot anomalies, and form hypotheses.
df.shape
df.info()
df.describe()
df["age"].mean()
df["salary"].median()
df["age"].hist()
df["gender"].value_counts()
df["department"].unique()
import seaborn as sns
sns.boxplot(df["salary"])
df.corr()
sns.heatmap(df.corr(), annot=True)
sns.pairplot(df)
df["income"].skew()
EDA gives you a strong understanding of your dataset and guides your feature engineering and model selection decisions.
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