This article was published as a part of the Data Science Blogathon.
Introduction
Python is an interpreted programming language used to build any Machine Learning or Deep Learning model. Data science aspirants need to have a good understanding of Python looking to work in the field of artificial intelligence.
So, if you are a fresher looking for a job role in data science, you must be very well prepared to answer Python-based interview questions. This article will cover coding questions on two main topics, i.e., zip() function and dataframe, frequently asked in interviews.
So let’s get started!
Python Coding Questions
Question 1: Given two lists, generate a list of pairs (one element from each list).
Suppose two lists are:
list1 = [1, 2, 3, 4]
list2 = [1, 4, 9, 16]
The below code can be used to create pairs using the zip() function.
zipped_list = zip(list1, list2) print(zipped_list) print(list(zipped_list))
The zip() function takes elements from each list one by one and pairs them up i.e., ‘1’ from list1 is paired with ‘1’ from list2 and so on.
Output:
[(1, 1), (2, 4), (3, 9), (4, 16)]
Question 2: Given two lists,
list1 = [“Ram”, “Shyam”, “Mohan”]
list2 = [24, 56, 34]
The output should be:
0 Ram 24
1 Shyam 56
2 Mohan 34
According to the given input and output, the task is to generate a dataframe from list1 and list2.
The above output can be achieved using the below code:
list1 = ["Ram", "Shyam", "Mohan"]
list2 = [24, 56, 34]
for x, (list1, list2) in enumerate(zip(list1, list2)):
print(x, list1, list2)
The zip() function makes pairs, taking elements index-wise from each list. Thus, the above code prints the index and elements from each list.
Output:
0 Ram 24 1 Shyam 56 2 Mohan 34
Question 3: Write a code snippet to design a Dictionary from two lists.
To design a dictionary, we need to take one element each from two lists and combine them iteratively as shown below:
list1 = [1, 2, 3, 4]
list2 = [1, 4, 9, 16]
dict1 = {list1: list2 for list1, list2 in zip(list1, list2)}
print(dict1)
The above code works at the element level, i.e., picking the first element of each list, grouping, and printing them. Then move to the second element of each list and again group and print them.
Output:
{1: 1, 2: 4, 3: 9, 4: 16}
Question 4: Given a list of pairs, say, [(1,1), (2,4),(3,9),(4,16)]. Write a code snippet to split into two sequences.
To achieve this, we need to unpair the items listed as shown below:
list_pair = [(1,1), (2,4),(3,9),(4,16)] num, square = zip(*list_pair) print(num) print(square)
Output:
(1, 2, 3, 4) (1, 4, 9, 16)
Question 5: Explain zip() function and its functionality.
Zip() is a Python function that combines two data (lists, tuples) into one. For instance,
data1 = [“Ram” ,”Shyam”] data2= [24, 56]
print(zip(data1, data2)
Question 6: What is DataFrame?
A DataFrame is a two-dimensional data structure consisting of rows, columns, and cells.
For instance-
S.No. Name Age
1 Ram 26
2 Shyam 28
3 Neha 36
Here, the first row represents that Ram has age 26 and so on.
Question 7: Discuss different ways of creating DataFrame.
There are different ways of creating DataFrame:
1. By using a single list
import pandas as pd data= ['Mumbai', 'Delhi', 'Pune'] df = pd.DataFrame(data) print(df)
Output:
0 0 Mumbai 1 Delhi 2 Pune
2. By using list of lists
import pandas as pd data= [['Mumbai', 6500], ['Delhi', 7000], ['Pune', 4000]] df = pd.DataFrame(data, columns =['City','Distance']) print(df)
Output:
City Distance 0 Mumbai 6500 1 Delhi 7000 2 Pune 4000
3. Create an empty DataFrame
df1 = pd.DataFrame(columns =[‘A’, ‘B’, ‘C])
This creates an empty dataframe with three columns A, B, and C.
Question 8: Write a code snippet to create a dataframe from the dictionary.
The dataframe can be created using the below code:
import pandas as pd
dict1 = {'Roll no':[1001, 1002, 1003],'Name' :['Geeta','Sita','Anjali']}
df = pd.DataFrame(dict1)
print (df)
The dictionary consists of key-value pairs. The key in the dictionary becomes the column name, and values become the entry on the cell of a particular column.
Output:
Roll no Name 0 1001 Geeta 1 1002 Sita 2 1003 Anjali
Question 9: How will you rename a column in DataFrame?
We can rename a column in a dataframe by using rename() function as shown below:
import pandas as pd
dict1 = {'Roll no':[1001, 1002, 1003],'Name' :['Geeta','Sita','Anjali']}
df = pd.DataFrame(dict1)
print (df)
df.rename(columns = {'Roll no':'S.no.'}, inplace = True)
print(df)
Output:
Roll no Name 0 1001 Geeta 1 1002 Sita 2 1003 Anjali S.no. Name 0 1001 Geeta 1 1002 Sita 2 1003 Anjali
We have renamed “Roll no.” as “S.no.”
Changing all column names
df.columns = ['Roll no', 'First Name'] print(df)
Output:
Roll no First Name 0 1001 Geeta 1 1002 Sita 2 1003 Anjali
Question 10: What is the difference between loc and iloc?
loc: It is label-based, i.e., rows and column names have to be provided to access an element of a dataframe.iloc: It is integer location-based, i.e., row number and column number have to be provided to access an element of a dataframe.
For eg, The given dataframe is:
Roll no Name Course
1 101 Ram Grad
2 102 Gorav Postgrad
3 103 Sita Grad
df.loc[‘1’, ‘Name’] will give you output as “Ram’.
df.iloc[0,1] will give you the output as “Ram’.
Question 11: How will you delete a row or column from the DataFrame?
The row or column of a DataFrame can be deleted by using the drop() function, i.e.if name of the dataframe is df; then the row can be deleted by using.
df.drop(['row_name'])
Similarly, the column can be deleted by using
df.drop(['column_name'])
Question 12: How do we sort a DataFrame?
The dataframe can be sorted using the command:
df.sort_values(by=['Name'])
The above command sorts the dataframe in ascending order.
df.sort_values(by=['Name'], ascending = False)
Question 13: Write a code snippet to add a new column in DataFrame.
A new column can be added using the below code:
import pandas as pd
dataframe = {'Roll no': [101, 102, 103],
'Name': ['Gorav', 'Riddhi', 'Shyama']}
df = pd.DataFrame(dataframe)
age = [24,25,26]
df['age'] = age
print(df)
One should know about the column name and its value for adding a new column. Then, the column can be added using df[‘column name’].
Output:
Roll no Name age 0 101 Gorav 24 1 102 Riddhi 25 2 103 Shyama 26
Helpful Tips
Source: TechBullion
- Dataframe and zip() are the two most important topics in any data scientist interview.
- One should be aware of the basics of dataframe before going for advanced topics.
- The creation, updation, and manipulation are important topics of dataframe. Therefore, any data science aspirant should be hand good grasp of the topic.
- Practice the basic questions on zip() before going for tough questions.
Conclusion
This article covered coding questions on zip() function and dataframe.
Following are takeaways:
- Zip() is used to combine two lists and is frequently used in combination with the dictionary.
- Dataframe is a two-dimensional data structure consisting of rows, columns, and cells.
- The difference between loc and iloc is a must-to-know. In loc, row and column name whereas in iloc row and column number is provided to access an element of the dataframe.
If you get a good grasp of these questions, you can also answer other Python coding questions that require using any of these two functionality provided by Python.
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