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import pandas as pd

DataFrame Operations – Indexing, Renaming, Querying, and Applying Functions

This notebook explores intermediate DataFrame operations using a James Bond films dataset. Topics include: setting and using custom indices with set_index(), label-based (loc[]) and position-based (iloc[]) row access, the deprecated ix[] accessor, modifying values in place, renaming columns with .rename(), dropping rows and columns with .drop(), random sampling with .sample(), finding extremes with .nlargest(), filtering with .where() and .query(), applying custom functions with .apply(), and understanding the difference between views and copies with .copy(). These are the building blocks for constructing complex data transformation pipelines.

bond = pd.read_csv("jamesbond.csv")
bond

bond.set_index("Film", inplace= True)

bond.loc["Goldfinger"]

bond = pd.read_csv("jamesbond.csv")

bond.loc[15]
bond.iloc[15]

bond.set_index("Film", inplace= True)
bond.sort_index(inplace = True)

bond.iloc[14]

bond.loc["Octopussy"]

bond.ix["Octopussy"]

bond.ix[14]

bond.loc["Octopussy",["Actor","Year"]]

bond.iloc[14,[1,2,4]]

bond.iloc[14,[1]] = "Sir Roger Moore"

bond["Actor"].unique()

mask = bond["Actor"] == "Sean Connery"

bond[mask]["Actor"] = "Sir Sean Connery"

df2 = bond["Actor"]
df2[mask]["Actor"] = "Sir Sean Connery"

df2

bond = pd.read_csv("jamesbond.csv")
bond.rename(columns={"Year":"Release Date"})

bond.columns

bond.drop("A View To Kill")

bond.drop("Box Office", axis = 1)

bond = pd.read_csv("jamesbond.csv")

bond.sample()

bond.sample(5)

bond.sample()

bond.sample(frac= .25)

bond.nlargest(n = 4 , columns= "Box Office")

bond = pd.read_csv("jamesbond.csv")

mask = bond["Actor"] == "Sean Connery"
bond[mask]

bond.where()

bond.columns = [column_name.replace(" ","_") for column_name in bond.columns]

bond.head()

bond.query("Box_Office > 500")

def convert_to_millions(number):
    return str(number) + " Millions!"

bond["Box Office"] = bond["Box Office"].apply(convert_to_millions)
bond["Box Office"]

directors = bond["Director"]

directors = bond["Director"].copy()

directors

directors["Sam Mendes"] = "Sit Sam Mendes"

directors

bond