📃 Pandas Data Manipulation.

Last Updated : 31th August 2025

---

Data manipulation is the process of manipulating and organizing data for analysis. Pandas provides various functions and methods for data manipulation, Some of the most important functions are-

---

Let Data is like this

import pandas as pd

df = pd.DataFrame({
    "Name": ["A", "B", "C", "D", "E", "F"],
    "Age": [20, 21, None, 22, 23, 24],
    "Marks": [85, 90, 95, 80, None, 70]
})

---

Sorting and Filtering

📊 Sorting.

# Sort by marks in ascending order
df.sort_values(by="Marks")

# Sort by multiple columns
df.sort_values(by=["Marks", "Age"], ascending=[False, True])

# Sort By index
df.sort_index()

# Ranking
# Rank based on marks
df["Rank"] = df["Marks"].rank(ascending=False)

# Rank based on marks and age
df["Rank"] = df[["Marks", "Age"]].rank(ascending=[False, True], method="min")

---

📊 Filtering.

import pandas as pd

# Students with Marks greater than 80

print(df[df["Marks"] > 80])

# Students with Marks greater than 80 and Age less than 25

print(df[(df["Marks"] > 80) & (df["Age"] < 25)])

# Students with Marks greater than 80 or Age less than 25

print(df[(df["Marks"] > 80) | (df["Age"] < 25)])

# Students who do NOT have Marks > 80
print(df[~(df["Marks"] > 80)])

Note use query() for Filtering Large Data.

# Filter by column name
df_filtered = df.query("Marks > 80 & Age < 22")

---

---