Practice Exploratory Data Analysis (eda) (6) - Exploratory Data Analysis

Practice: Exploratory Data Analysis (EDA)

Lesson 6Exploratory Data Analysis

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10 questions

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4 cards from this section. Quick, good the night before a test.
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6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does the df.shape function return?
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Think about how many rows and columns the data has.
Question 2.
Which library in Python is primarily used for data visualization?
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Remember the library that starts with 'M' for graphs.
3Question 3.
What does Exploratory Data Analysis (EDA) primarily help with?
- Building models
- Understanding data
- Cleaning data
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Think about the first step of data examination.
4Question 4.
True or False: Visualization is not important in EDA.
- True
- False
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Recall the various visual tools we've discussed.
Question 5.
Given a dataset with age and salary, create a scatter plot using Matplotlib. Interpret the correlation and identify whether it is strong or weak.
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Look for the direction and clustering of points when you plot.
Question 6.
Using a dataset of your choice, generate a full EDA report with Pandas Profiling. List the insights you gather from this report.
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Pay attention to the sections concerning missing data and distributions.

6 more questions in this section. Enroll free to practise them all.