Pandas Interview Questions

Checkout Vskills Interview questions with answers in Pandas to prepare for your next job role. The questions are submitted by professionals to help you to prepare for the Interview.

Q.1 What do you understand by Pandas?
Pandas is a Python language package which gives fast, flexible, and expressive data structures for processing relational or labelled data easily thus, helping in data analysis. Pandas is free software released under the three-clause BSD license.
Q.2 What is the utility of Python pandas?
Pandas is a Python programming language library which is used for data manipulation and analysis by providing data structures and operations for manipulating numerical tables and time series.
Q.3 What do you understand by a Series in Pandas?
Pandas Series refers to a one-dimensional array which can store data of any type (integer, string, float, python objects, etc.) similar to a column in an excel sheet.
Q.4 What is the use of Reindexing in Pandas?
Reindexing in Pandas reorders the existing data to match a new set of labels, inserts missing value (NA) markers in label locations where no data for that label existed and if specified, fill data for missing labels using logic (highly relevant to working with time series data)
Q.5 What will list the top rows of the frame in Pandas?
In Pandas, df.head() will list the top rows of the frame
Q.6 List the different Types of Data structures in pandas?
There are 2 data structures in pandas: Series and DataFrames which are built on top of Numpy. Series is a one-dimensional data structure in pandas and DataFrame is the two-dimensional data structure.
Q.7 How to create copy of series in Pandas?
The Series.copy() will create copy of series in Pandas.
Q.8 What do you understand by Time Series in pandas?
A time series in pandas refers to an ordered sequence of data representing changes over time.
Q.9 How does pandas supports Time Series data?
Pandas supports Time Series data by offering parsing capability for time series information from various sources and formats, generating sequences of fixed-frequency dates and time spans, ability to manipulate and convert date time with timezone information as well as resampling or converting a time series to a particular frequency with ability to perform date and time arithmetic with absolute or relative time increments
Q.10 What do you understand by Categorical Data in Pandas?
Categorical Data in Pandas refers to categorical variables in statistics which takes on a limited and usually fixed, number of possible values like gender, social class, blood type, country affiliation, etc. Values of categorical data are either in categories or np.nan.
Q.11 How Categorical Data in Pandas is used?
The Categorical Data in Pandas is useful in various use cases like by converting to a categorical and specifying an order on the categories, sorting and min/max will use the logical order instead of the lexical order or converting a string variable having only a few different values to a categorical variable to save memory and also as a signal to other Python libraries that this column should be treated as a categorical variable.
Q.12 How to create a series in Pandas from dict in Python?
To create a series in Pandas from dict in Python, we will use Series() method without index parameter.
Q.13 What do you understand by a DataFrame in pandas?
DataFrame in pandas is a 2-dimensional size-mutable, usually heterogeneous tabular data structure having labelled axes or rows and columns. A Data frame has 3 components- the data, rows, and columns.
Q.14 How to create a Pandas DataFrame?
A Pandas DataFrame can be created by loading the datasets from datasets like SQL Database, CSV file, and Excel file or from the lists, dictionary, list of dictionary etc.
Q.15 How to create an empty DataFrame in pandas?
The DataFrame() function creates a empty Pandas dataframe as: pd.DataFrame() and for an empty dataframe with three empty column (columns X, Y and Z)- pd.DataFrame(columns=[‘X’, ‘Y’, ‘Z’])
Q.16 How to delete columns from a Pandas Data Frame?
The drop() method is used for deleting a column from the DataFrame and the axis argument is either 0 if it indicates the rows and 1 if it drops the columns.
Q.17 How to Delete the duplicate values from the columns from a Pandas Data Frame?
In Pandas, to delete the duplicate values from the column use the drop_duplicates() method.
Q.18 How to Delete remove duplicate rows from the Pandas Data Frame?
In Pandas, to delete the duplicate rows from the Pandas Data Frame, we use df.drop_duplicates() method.
Q.19 Which pandas library is used to create a scatter plot matrix?
The Scatter_matrix pandas library is used to create a scatter plot matrix
Q.20 What is pylab?
PyLab is a package that contains NumPy, SciPy, and Matplotlib into a single namespace.
Q.21 What is used for styling in Pandas?
The styling in Pandas is accomplished using CSS
Q.22 What will iterate over a Pandas DataFrame?
We can iterate on the rows of the DataFrame by using for loop in combination along with calling the iterrows() function on the DataFrame.
Q.23 What will output the items of series A not present in series B in Pandas?
We use the isin() method in Pandas to get the items of series A not present in series B
Q.24 How you keep yourself updated of new trends in Pandas?
Pandas and data science are seeing newer development every year and I update myself by attending industry seminars, conferences as available online or offline.
Q.25 How do you see yourself in next five year in Pandas?
I foresee a bright future as I will gain more skills and knowledge in the domain of Pandas and data science by adding new technologies as needed by my organization.
Q.26 What are your strengths as a Pandas professional?
As a Pandas professional I am having extensive experience on the new data science technologies as well as managing the Pandas and Python. I also have the requisite managerial skills for managing team and achieve the assigned tasks.
Q.27 How do you prioritize Pandas related tasks?
Pandas based data analysis involves many tasks on a day to day basis. Tasks also need to be prioritized to accomplish the organizational goals as per the specified KPIs (key performance indicators). Prioritization of tasks is done on the basis of various factors like: the tasks relevance, urgency, cost involved and resource availability.
Q.28 How you manage your time for Pandas related development?
Pandas based data analysis involves lots of tasks which need to be completed in a specific time frame. Hence time management is of utmost importance and is applied by: using to do lists, being aware of time wasters and optimizing work environment
Q.29 Why do you want the Pandas job?
I want the Pandas job as I am passionate about making companies more efficient by using new data analysis technologies especially Pandas and also take stock of present technology portfolio to maximize their utility.
Q.30 What do you think of most important role of a Pandas professional?
As a Pandas professional my focus is to provide the effective and efficient programs and data analysis using pandas so as to fulfil the data analysis or data science related need. Adopting technologies which are more efficient and effective for the organization. Reducing costs without losing on quality or speed of production is the primary motto.
Get Govt. Certified Take Test