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Data Analysis with Pandas and Python Certification

About the Quiz

Get Data Analysis with Pandas and Python Certificate from The Digital Adda which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

Exam Details

  • Format: Multiple Choice Question
  • Questions: 10
  • Passing Score: 8/10 or 80%
  • Language: English

Here are the questions and answers

Which of the following feature is not provided by the Pandas module?

Merge and join the data sets
Filter data using the condition
Plot and visualize the data
Perform Arithmetic Operations on Columns

From which of the following files, pandas can read data?

JSON
Excel
HTML
All the above

Given a dataset named ‘data’ containing the 5 columns and 10 rows, find the output of the below code?
print(len(data.columns))

5
10
15
20

Which of the following commands return the data type of the values in each column in the data frame df?

print(df.dtype)
print(dtypes(df))
print(df.dtypes)
None of the above

What does the attribute shape return?

It returns the number of rows and columns respectively in the form of a tuple
It returns the number of columns and rows respectively in the form of a list
It returns the number of rows and columns respectively in the form of a list
It returns the number of columns and rows respectively in the form of a tuple

By default, number of rows are returned by the head() and tail() function?

10,10
5,5
10,5
5,10

Which of the following can be stored in a dataframe?

a two-dimensional ndarray
lists, dictionaries, or Series.
Pandas DataFrame
All the above

What is the output of the following code?

print(df.iloc[2:5])

prints the 2nd, 3rd,4th,5th columns of the dataframe df
prints the 2nd, 3rd,4th columns of the dataframe df
prints the 2nd, 3rd,4th rows of the dataframe df
prints the 2nd, 3rd,4th,5th rows of the dataframe df

Which of the following changes the data type of a column named item in data frame df to string datatype?

df.item.astype(str)
df.item.type(str)
str(df.item)
None of the above

Which of the following commands remove missing values?

df.dropna()

df.removena
df.removenull()
df.delnull()

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