Pandas and Matplot Quiz

What is the primary data structure in pandas for storing one-dimensional data?

• Series

• DataFrame

• List

• Array

Answer explanation

The primary data structure in pandas for storing one-dimensional data is a Series. It is designed to hold a single column of data, making it ideal for this purpose, unlike DataFrames which store two-dimensional data.

Which pandas function is used to read a CSV file into a DataFrame?

• load_csv

• open_csv

• read_csv

• import_csv

Answer explanation

The correct function to read a CSV file into a DataFrame in pandas is 'read_csv'. The other options, 'load_csv', 'open_csv', and 'import_csv', do not exist in the pandas library.

What is the method used to create a line plot in matplotlib?

• plt.scatter()

• plt.bar()

• plt.pie()

• plt.plot()

Answer explanation

The correct method to create a line plot in matplotlib is plt.plot(). This function is specifically designed for plotting lines, while plt.scatter() is for scatter plots, plt.bar() for bar charts, and plt.pie() for pie charts.

What is the key difference between a pandas Series and a DataFrame?

• A Series is used for numerical data only, while a DataFrame can handle both numerical and categorical data

• A Series can only contain one data type, while a DataFrame can contain multiple data types

• The key difference is that a Series is one-dimensional and a DataFrame is two-dimensional.

• A Series can only have one index, while a DataFrame can have multiple indexes

Answer explanation

The key difference is that a Series is one-dimensional, representing a single column of data, while a DataFrame is two-dimensional, consisting of multiple columns and rows, allowing for more complex data structures.

Which pandas function is used to calculate the average of a DataFrame?

• mean

• average

• median

• mode

Answer explanation

The correct function to calculate the average of a DataFrame in pandas is 'mean'. The 'average' function does not exist in pandas, while 'median' and 'mode' calculate different statistical measures.

What is the purpose of the 'groupby' function in pandas?

• To filter out null values from the data

• To calculate the mean of the data

• To sort the data in ascending order

• To group data together based on a specific column or columns.

Answer explanation

The 'groupby' function in pandas is used to group data together based on one or more specific columns. This allows for aggregation and analysis of data subsets, making it a powerful tool for data manipulation.

What is the method used to create a scatter plot in matplotlib?

• plt.plot()

• plt.bar()

• plt.scatter()

• plt.pie()

Answer explanation

The correct method to create a scatter plot in matplotlib is plt.scatter(). This function specifically plots points on a Cartesian plane, making it ideal for visualizing the relationship between two variables.

What is the primary use of the 'describe' function in pandas?

• To sort the data in ascending order

• To generate descriptive statistics of the data

• To create a new column in the dataframe

• To remove duplicate rows from the dataframe

Answer explanation

The 'describe' function in pandas is primarily used to generate descriptive statistics of the data, such as count, mean, standard deviation, and percentiles, providing a quick overview of the dataset.

What is the main difference between 'loc' and 'iloc' in pandas?

• 'loc' is label-based, while 'iloc' is integer position-based

• 'loc' is used for data cleaning, while 'iloc' is used for data visualization

• 'loc' is used for data visualization, while 'iloc' is used for data cleaning

• 'loc' and 'iloc' are the same in pandas

Answer explanation

The main difference is that 'loc' is label-based, allowing access to rows and columns using their labels, while 'iloc' is integer position-based, allowing access using integer indices. This makes 'loc' suitable for label-specific operations.

Which of the following is true about 'iloc' in pandas?

• 'iloc' stands for 'integer location' and it is used for indexing by integer location

• 'iloc' stands for 'index location' and it is used for indexing by label location

• 'iloc' stands for 'integer location' and it is used for indexing by label location

• 'iloc' stands for 'index location' and it is used for indexing by integer location

Answer explanation

'iloc' stands for 'integer location' and is specifically used for indexing by integer positions in a DataFrame or Series, making the first answer choice correct.