Outlier detection with IQR in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does IQR stand for in data analysis?

IQR stands for Interquartile Range. It measures the middle 50% spread of the data between the 25th percentile (Q1) and the 75th percentile (Q3).

beginner

How do you calculate the IQR from a dataset?

IQR = Q3 - Q1, where Q1 is the 25th percentile and Q3 is the 75th percentile of the data.

intermediate

Why is IQR useful for detecting outliers?

IQR helps find outliers by identifying data points that fall below Q1 - 1.5*IQR or above Q3 + 1.5*IQR, which are unusually far from the middle 50% of data.

beginner

Show the pandas code to calculate Q1, Q3, and IQR for a DataFrame column named 'data'.

Q1 = df['data'].quantile(0.25) Q3 = df['data'].quantile(0.75) IQR = Q3 - Q1

intermediate

How do you filter out outliers using IQR in pandas?

Use the condition: keep rows where values are >= Q1 - 1.5*IQR and <= Q3 + 1.5*IQR. Example: filtered_df = df[(df['data'] >= Q1 - 1.5*IQR) & (df['data'] <= Q3 + 1.5*IQR)]

What does the IQR measure in a dataset?

A The range between minimum and maximum values

B The average value

C The total number of data points

D The middle 50% spread of the data

IQR measures the spread between the 25th percentile (Q1) and 75th percentile (Q3), which covers the middle 50% of the data.

Which formula identifies outliers using IQR?

A Values < Q1 - 1.5*IQR or > Q3 + 1.5*IQR

B Values < Q1 + 1.5*IQR or > Q3 - 1.5*IQR

C Values < mean - 2*std or > mean + 2*std

D Values < minimum or > maximum

Outliers are values that fall below Q1 minus 1.5 times the IQR or above Q3 plus 1.5 times the IQR.

In pandas, how do you get the 25th percentile of a column 'data'?

A df['data'].mean()

B df['data'].quantile(0.25)

C df['data'].median()

D df['data'].max()

The quantile method with 0.25 returns the 25th percentile (Q1) of the column.

What is the purpose of filtering data using IQR in pandas?

A To remove missing values

B To select only the largest values

C To remove outliers

D To sort the data

Filtering with IQR helps remove outliers that are unusually far from the central data range.

If Q1 = 10 and Q3 = 20, what is the IQR?

A 10

B 30

C 15

D 20

IQR = Q3 - Q1 = 20 - 10 = 10.

Explain how to detect outliers using the IQR method in pandas.

Think about the steps from calculating quartiles to filtering data.

Why is the IQR method preferred over using min and max values for outlier detection?

Consider how extreme values affect range versus IQR.