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Data Analysis Pythondata~5 mins

Correlation with corr() in Data Analysis Python - Cheat Sheet & Quick Revision

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Recall & Review
beginner
What does the corr() function do in data analysis?
The corr() function calculates the correlation between columns in a dataset, showing how strongly two variables move together.
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beginner
What type of values does corr() return?
It returns values between -1 and 1, where 1 means perfect positive correlation, -1 means perfect negative correlation, and 0 means no correlation.
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beginner
How can you interpret a correlation value of 0.8 between two variables?
A value of 0.8 means a strong positive relationship; as one variable increases, the other tends to increase too.
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beginner
Which Python library provides the corr() function for dataframes?
The pandas library provides the corr() function to calculate correlation between dataframe columns.
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beginner
Can corr() handle non-numeric data?
No, corr() only works with numeric data columns. Non-numeric columns are ignored.
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What does a correlation value of -1 indicate?
APerfect positive correlation
BNo correlation
CPerfect negative correlation
DWeak correlation
Which Python library do you use to call corr() on a dataframe?
ANumPy
Bpandas
Cmatplotlib
Dscikit-learn
If two variables have a correlation close to 0, what does it mean?
APerfect correlation
BStrong negative relationship
CStrong positive relationship
DNo linear relationship
What kind of data does corr() require?
ANumeric data
BDate data
CText data
DCategorical data
Which of these correlation values shows the strongest relationship?
A-0.9
B0.3
C0.5
D-0.2
Explain what correlation means and how the corr() function helps in data analysis.
Think about how two things can move together or opposite.
You got /4 concepts.
    Describe how to interpret a correlation matrix output from corr().
    Imagine a table showing how each pair of columns relate.
    You got /4 concepts.