Programming Part 2

Question 1

What is a DataFrame in pandas?

Answer 1

A two-dimensional labeled data structure similar to a table.

Question 2

What is a Series in pandas?

Answer 2

A one-dimensional labeled array.

Question 3

How do you read a CSV into a pandas DataFrame?

Answer 3

Using pd.read_csv(‘filename.csv’)

Question 4

How do you inspect the first few rows of a DataFrame?

Answer 4

Using the .head() method.

Question 5

How do you get column names from a DataFrame?

Answer 5

Using df.columns

Question 6

How do you select a column from a DataFrame?

Answer 6

Using df[‘column_name’]

Question 7

How do you select multiple columns?

Answer 7

Using df[[‘col1’, ‘col2’]]

Question 8

What is .loc[] used for in pandas?

Answer 8

Label-based indexing for rows and columns.

Question 9

What is .iloc[] used for in pandas?

Answer 9

Position-based indexing for rows and columns.

Question 10

How do you filter rows based on a condition?

Answer 10

Using boolean indexing: df[df[‘column’] > value]

Question 11

How do you check for missing values?

Answer 11

Using df.isnull()

Question 12

How do you drop rows with missing values?

Answer 12

Using df.dropna()

Question 13

How do you fill missing values?

Answer 13

Using df.fillna(value)

Question 14

How do you rename columns in pandas?

Answer 14

Using df.rename(columns={‘old’: ‘new’})

Question 15

How do you change the data type of a column?

Answer 15

Using df[‘col’] = df[‘col’].astype(new_type)

Question 16

What does .groupby() do?

Answer 16

Groups rows based on column values for aggregation.

Question 17

How do you calculate mean for each group?

Answer 17

df.groupby(‘col’).mean()

Question 18

What is the purpose of .agg()?

Answer 18

To apply multiple aggregation functions at once.

Question 19

How do you count unique values in a column?

Answer 19

Using df[‘col’].nunique()

Question 20

What does df.value_counts() do?

Answer 20

Counts occurrences of unique values in a Series.

Question 21

How do you concatenate two DataFrames?

Answer 21

Using pd.concat([df1, df2])

Question 22

How do you merge two DataFrames?

Answer 22

Using pd.merge(df1, df2, on=’key’)

Question 23

What is the difference between merge and join in pandas?

Answer 23

merge is a method; join is an attribute method for DataFrames.

Question 24

How do you reset the index of a DataFrame?

Answer 24

Using df.reset_index()

Question 25

How do you set a column as the index?

Answer 25

Using df.set_index('column')