Impara Working with Duplicates

AI in Action

import pandas as pd

df = pd.read_csv("passengers.csv")

print(df.duplicated().sum())
df = df.drop_duplicates()

Detecting Duplicates

You can check for duplicates in a DataFrame using the .duplicated() method. You can also use it to count how many rows are duplicates.


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Check which rows are duplicates
print(df.duplicated())
# Count duplicate rows
print(df.duplicated().sum())

By default, pandas checks all columns when identifying duplicates. You can also check duplicates within a specific subset of columns:


              12345
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

print(df.duplicated(subset=["Ticket"]).sum())

Removing Duplicates

After you confirm that the duplicate rows shouldn't remain, remove them using the .drop_duplicates() method:


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Remove duplicate rows
print(df.drop_duplicates())
# Remove duplicates based only on values in a subset
print(df.drop_duplicates(subset=["Ticket"]))

Counting Unique Values

To check how many distinct values each column has, use the .nunique() method:


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Count unique values for each column
print(df.nunique())
# Count unique values for a single column
print(df["Embarked"].nunique())

This helps you identify columns with limited categories or verify whether an ID column is truly unique.

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Grazie per i tuoi commenti!

Sezione 2. Capitolo 2

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AI in Action

import pandas as pd

df = pd.read_csv("passengers.csv")

print(df.duplicated().sum())
df = df.drop_duplicates()

Detecting Duplicates

You can check for duplicates in a DataFrame using the .duplicated() method. You can also use it to count how many rows are duplicates.


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Check which rows are duplicates
print(df.duplicated())
# Count duplicate rows
print(df.duplicated().sum())

By default, pandas checks all columns when identifying duplicates. You can also check duplicates within a specific subset of columns:


              12345
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

print(df.duplicated(subset=["Ticket"]).sum())

Removing Duplicates

After you confirm that the duplicate rows shouldn't remain, remove them using the .drop_duplicates() method:


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Remove duplicate rows
print(df.drop_duplicates())
# Remove duplicates based only on values in a subset
print(df.drop_duplicates(subset=["Ticket"]))

Counting Unique Values

To check how many distinct values each column has, use the .nunique() method:


              12345678
            
import pandas as pd

df = pd.read_csv("https://staging-content-media-cdn.codefinity.com/courses/64641555-cae4-4cd0-8d29-807aeb6bc0c4/datasets/passengers.csv")

# Count unique values for each column
print(df.nunique())
# Count unique values for a single column
print(df["Embarked"].nunique())

This helps you identify columns with limited categories or verify whether an ID column is truly unique.

Tutto è chiaro?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 2

Working with Duplicates

AI in Action

Detecting Duplicates

Removing Duplicates

Counting Unique Values

1. What does `df.duplicated()` return?

2. How can you remove all duplicate rows from a DataFrame?

3. How would you count a number of unique elements in the `"Class"` column?

Working with Duplicates

AI in Action

Detecting Duplicates

Removing Duplicates

Counting Unique Values

1. What does `df.duplicated()` return?

2. How can you remove all duplicate rows from a DataFrame?

3. How would you count a number of unique elements in the `"Class"` column?

Working with Duplicates

AI in Action

Detecting Duplicates

Removing Duplicates

Counting Unique Values

1. What does df.duplicated() return?

2. How can you remove all duplicate rows from a DataFrame?

3. How would you count a number of unique elements in the "Class" column?

Working with Duplicates

AI in Action

Detecting Duplicates

Removing Duplicates

Counting Unique Values

1. What does df.duplicated() return?

2. How can you remove all duplicate rows from a DataFrame?

3. How would you count a number of unique elements in the "Class" column?

1. What does `df.duplicated()` return?

3. How would you count a number of unique elements in the `"Class"` column?

1. What does `df.duplicated()` return?

3. How would you count a number of unique elements in the `"Class"` column?