# ---------- 1. Primitives ----------print("=== String ===")print("Hello World")print("\n=== Integer ===")print(42)print("\n=== Float ===")print(3.14)# ---------- 2. Simple Containers ----------print("\n=== List ===")simple_list= [1,2,3,"hello"]print(simple_list)print("\n=== Dict ===")simple_dict= {"name":"John","age":25,"city":"NYC"}print(simple_dict)# ---------- 3. f-Strings ----------print("\n=== f-String (list) ===")print(f"List:{simple_list}")print("\n=== f-String (dict) ===")print(f"Dict:{simple_dict}")# ---------- 4. NumPy ----------importnumpyasnpprint("\n=== NumPy 1-D ===")np_1d=np.array([1,2,3,4,5])print(np_1d)print("\n=== NumPy 2-D ===")np_2d=np.arange(12).reshape(3,4)print(np_2d)# ---------- 5. Pandas – Basic ----------importpandasaspdprint("\n=== DataFrame (simple) ===")df_simple=pd.DataFrame({"name": ["Alice","Bob"],"age": [25,30]})print(df_simple)# ---------- 6. Pandas – MultiIndex ----------print("\n=== DataFrame (groupby MultiIndex) ===")sales=pd.DataFrame({"region": ["North","North","South","South"],"product": ["A","B","A","B"],"sales": [100,150,200,120],})grouped=sales.groupby("region").agg({"sales": ["sum","mean"]})print(grouped)# ---------- 7. Pandas – Pivot Table ----------print("\n=== Pivot Table ===")pivot=sales.pivot_table(values="sales",index="region",columns="product",aggfunc="sum")print(pivot)# ---------- 8. Complex MultiIndex ----------print("\n=== Triple-level MultiIndex ===")big=pd.DataFrame({"region": ["N","N","N","S","S","S"]*2,"product": ["A","A","B","A","A","B"]*2,"quarter": ["Q1","Q2"]*6,"sales":range(12),"profit":range(12,24),})triple=big.groupby(["region","product","quarter"]).agg({"sales": ["sum","mean"],"profit":"sum"})print(triple)# ---------- 9. Containers of DataFrames ----------print("\n=== List of DataFrames ===")df_list= [df_simple,grouped]print(df_list)print("\n=== Dict of DataFrames ===")df_dict= {"customers":df_simple,"sales_summary":grouped}print(df_dict)# ---------- 10. Mixed Bag ----------print("\n=== Mixed List ===")mixed= [df_simple,np_1d,"text",42]print(mixed)