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Q & A – Pandas Advance Interview Questions
(1) Difference Between “apply()” and “applymap()” Method In Pandas. Main difference between “apply()” and “applymap()” is that, “apply()” method applies the function entirely by taking a row or column as an argument. “applymap()” method applies the function elementwise to each row or each column. Example import pandas as pd df1 = pd.DataFrame({‘names’: [‘Subrat’, ‘Arpita’, ‘Abhispa’, ‘Subhada’, ‘Sonali’], ‘marks’: [67, 75, 84, 90, 99]}) df1 df1.apply(lambda x:len(x)) Output: Note: Here ‘5’ represents the total elements inside the ‘name’ and ‘marks’ columns. Here apply() considered ‘name’ and ‘column’ as a series and calculated its length. df1.applymap(lambda x: len(str(x))) Output: Note: Here applymap()
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Q & A – Pandas Basics
(1) What Is Pandas In Python? Pandas is an open-source, python-based library used in data manipulation applications requiring high performance. The name is derived from “Panel Data” having multidimensional data. This was developed in 2008 by Wes McKinney and was developed for data analysis. Pandas are useful in performing 5 major steps of data analysis – Load the data, clean/manipulate it, prepare it, model it, and analyze the data. (2) Define Pandas dataFrame? A data frame is a 2D mutable and tabular structure for representing data labelled with axes – rows and columns. The syntax for creating a data frame:
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Pandas – Interview Questions
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