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Interview Questions in Pandas

Q-1) What is Pandas in Python?

  • Pandas is referred to as an open-source library that offers high-performance data manipulation in Python. The term Panel Data, which denotes a Structural equation model from Multidimensional Data, is where the name Pandas originates.

Q-2) What are the different types of Data Structures in Pandas?

  • Pandas provide two data structures, Series and DataFrames, which are supported by the pandas library. Both of these data structures are based on NumPy. In Pandas, a Series is a one-dimensional data structure, whereas a DataFrame is a two-dimensional data structure.

Q-3) Define DataFrames?

  • One of the pandas' most popular data structures, the DataFrame, uses a two-dimensional array with named axes (rows and columns) As a common method of storing data, DataFrame has two separate indexes: row index and column index.

Q-4) What are the features of pandas that are significant?

  • The key features are:
    • Memory Efficient
    • Time Series
    • Reshaping
    • Merge and join
    • Data Alignment

Q-5) Define Series in Pandas?

  • A Series is a one-dimensional array that can store a variety of data types. The index refers to the row labels of a series. We can easily convert a list, tuple, or dictionary into a series by using the 'series' method. A Series cannot have more than one column.

Q-6) What is categorical data in Pandas?

  • A categorical data is described as corresponding to a statistical categorical variable. A categorical variable often only has a small, typically set range of possible values.

Q-7) What is the name of Pandas library tools used to create a scatter plot matrix?

  • Scatter_matrix

Q-8) What are the different ways a DataFrame can be created in pandas?

  • There are following 2 ways:
    • List
    • Dict of arrays

Q-9) How to convert a numpy array to a dataframe?

  • p = pd.Series(np.random.randint(1, 7, 35))  
    info = pd.DataFrame(p.values.reshape(7,5)) 

    Output:

    0  1  2  3  4
    0  3  2  5  5  1
    1  3  2  5  5  5
    2  1  3  1  2  6
    3  1  1  1  2  2
    4  3  5  3  3  3
    5  2  5  3  6  4
    6  3  6  6  6  5

Q-10) How to convert DataFrame into Numpy array?

  • We can convert Pandas DataFrames to numpy arrays to perform some high-level mathematical functions. It makes use of the DataFrame.to_numpy() method.

  • The DataFrame.to_numpy() function is used to return a numpy ndarray.

Q-11) Pandas Index?

  • A crucial tool that chooses specific rows and columns of data from a DataFrame is called a Pandas Index.

Q-12) Whar are the Data Operations in Pandas?

  • There are following useful data operations in pandas:
    • Row and column selection
    • Filter Data
    • Null Values

Q-13) What is GroupBy in Pandas?

  • By using them on actual data sets, the Pandas groupby() method enables us to reorder the data. Its main duty is to divide the data into numerous categories.