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Viewing 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

bookViewing the Data

To view the first few rows of a dataset in Python, we can utilize the head() method. This function accepts an integer as its argument, which specifies the number of rows to display (by default, it shows first 5 rows). Let's take a look at the first 10 rows of our dataset:

If we want to see the last few rows of a dataframe, we can use the tail() method. It works similarly to the head() method:

Another useful function for exploring dataframes is sample(). This function fetches random records from a dataframe. By default, it retrieves a single random record unless specified otherwise.

Task
test

Swipe to show code editor

We have a dataframe named frame.

  1. We need to extract the first 10 rows from this dataframe.
  2. We need to retrieve the last 15 rows from this dataframe.
  3. We want to select a random sample of 12 rows from this dataframe.

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Section 3. Chapter 1
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bookViewing the Data

To view the first few rows of a dataset in Python, we can utilize the head() method. This function accepts an integer as its argument, which specifies the number of rows to display (by default, it shows first 5 rows). Let's take a look at the first 10 rows of our dataset:

If we want to see the last few rows of a dataframe, we can use the tail() method. It works similarly to the head() method:

Another useful function for exploring dataframes is sample(). This function fetches random records from a dataframe. By default, it retrieves a single random record unless specified otherwise.

Task
test

Swipe to show code editor

We have a dataframe named frame.

  1. We need to extract the first 10 rows from this dataframe.
  2. We need to retrieve the last 15 rows from this dataframe.
  3. We want to select a random sample of 12 rows from this dataframe.

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 1
toggle bottom row

bookViewing the Data

To view the first few rows of a dataset in Python, we can utilize the head() method. This function accepts an integer as its argument, which specifies the number of rows to display (by default, it shows first 5 rows). Let's take a look at the first 10 rows of our dataset:

If we want to see the last few rows of a dataframe, we can use the tail() method. It works similarly to the head() method:

Another useful function for exploring dataframes is sample(). This function fetches random records from a dataframe. By default, it retrieves a single random record unless specified otherwise.

Task
test

Swipe to show code editor

We have a dataframe named frame.

  1. We need to extract the first 10 rows from this dataframe.
  2. We need to retrieve the last 15 rows from this dataframe.
  3. We want to select a random sample of 12 rows from this dataframe.

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!

To view the first few rows of a dataset in Python, we can utilize the head() method. This function accepts an integer as its argument, which specifies the number of rows to display (by default, it shows first 5 rows). Let's take a look at the first 10 rows of our dataset:

If we want to see the last few rows of a dataframe, we can use the tail() method. It works similarly to the head() method:

Another useful function for exploring dataframes is sample(). This function fetches random records from a dataframe. By default, it retrieves a single random record unless specified otherwise.

Task
test

Swipe to show code editor

We have a dataframe named frame.

  1. We need to extract the first 10 rows from this dataframe.
  2. We need to retrieve the last 15 rows from this dataframe.
  3. We want to select a random sample of 12 rows from this dataframe.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 1
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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