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Learn Describing the Data | Analyzing the Data
Pandas First Steps
course content

Course Content

Pandas First Steps

Pandas First Steps

1. The Very First Steps
2. Reading Files in Pandas
3. Analyzing the Data

book
Describing the Data

pandas offers the handy mean() method that calculates the average of all values for each column.

python

You can also the same method to determine the average value for a specific column:

python

pandas also provides the mode() method, which identifies the most frequently occurring value in each column.

python

To find the mode for a particular column, the same method is used:

python

Another useful method in pandas is describe().

python

This method provides an overview of various metrics from the dataset, including:

  • Total number of entries;
  • Mean or average value;
  • Standard deviation;
  • The minimum and maximum values;
  • The 25th, 50th (median), and 75th percentiles.
Task

Swipe to start coding

You are given a DataFrame named wine_data.

  • Calculate the mean of the 'residual sugar' column and store the result in the residual_sugar_mean variable.
  • Calculate the mode of the 'fixed acidity' column and store the result in the fixed_acidity_mode variable.
  • Retrieve an overview of various statistics from wine_data and store the result in the described_data variable.

Solution

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Section 3. Chapter 11
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book
Describing the Data

pandas offers the handy mean() method that calculates the average of all values for each column.

python

You can also the same method to determine the average value for a specific column:

python

pandas also provides the mode() method, which identifies the most frequently occurring value in each column.

python

To find the mode for a particular column, the same method is used:

python

Another useful method in pandas is describe().

python

This method provides an overview of various metrics from the dataset, including:

  • Total number of entries;
  • Mean or average value;
  • Standard deviation;
  • The minimum and maximum values;
  • The 25th, 50th (median), and 75th percentiles.
Task

Swipe to start coding

You are given a DataFrame named wine_data.

  • Calculate the mean of the 'residual sugar' column and store the result in the residual_sugar_mean variable.
  • Calculate the mode of the 'fixed acidity' column and store the result in the fixed_acidity_mode variable.
  • Retrieve an overview of various statistics from wine_data and store the result in the described_data variable.

Solution

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 3. Chapter 11
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