Pandas Part 2

What is a Pandas Series?

• A Pandas Series is a one-dimensional labeled array in Python's Pandas library.

• A Pandas Series is a collection of functions in the Pandas library.

• A Pandas Series is a type of database in Python.

• A Pandas Series is a two-dimensional labeled array.

How do you create a Pandas Series from a Python list?

• import pandas as pd

  my_series = pd.Series({'a': 1, 'b': 2})

• import pandas as pd

  my_series = pd.Series(range(3))

• import pandas as pd

  my_series = pd.Series(1, 2, 3)

• import pandas as pd

  my_list = [1, 2, 3]

  my_series = pd.Series(my_list)

What is the purpose of custom indexing(or labels) in Pandas Series?

• To identify data type of elements across the Series.

• To reduce the memory usage of the Series.

• To automatically sort the data in ascending order.

• The purpose of custom indexing in Pandas Series is to provide meaningful labels for elements

How can you assign a custom index to a Pandas Series?

• pd.Series([1, 2, 3], index=["a", "b", "c"])

• pd.Series([1, 2, 3], columns=["a", "b", "c"])

• pd.Series([1, 2, 3], labels=["a", "b", "c"])

• pd.Series([1, 2, 3], label_index=["a", "b", "c"])

What is the difference between a Pandas Series and a NumPy array?

• A Pandas Series does not support indexing, while a NumPy array does.

• A Pandas Series can only hold numerical data, while a NumPy array can hold mixed data types.

• A Pandas Series is labeled and can hold mixed data types, while a NumPy array is homogeneous and optimized for mathematical operations.

How do you assign custom labels to a Pandas Series?

• Use the 'label' method of the Series to assign custom labels.

• Use the 'index' attribute of the Series to assign custom labels.

• Use the 'rename' function to set custom labels for the Series.

Can a Pandas Series have non-numeric labels? Give an example.

• Yes, but only with boolean labels like True and False.

• No, a Pandas Series can only have numeric labels.

• Yes, a Pandas Series can have non-numeric labels. Example: pd.Series([1, 2, 3], index=['apple', 'banana', 'cherry'])

What method would you use to convert a Python list into a Pandas Series?

• your_list.to_series()

• pd.Series(your_list)

• list.to_series()

• pd.convert_to_series(your_list)

What is the main feature of a Pandas Series?

• It is similar to a NumPy array, but with labeled axes (indexes).

• It can only store numerical data.

• It can only store text data.

How can you access the element with the index 'B' in the following Series?

• series['B']

• series.B

• series[1]

• series.get('B')