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TXT Files | Reading Files in Pandas
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

TXT Files

Text files are another common data format, and the pandas library makes it easy to work with them — often more straightforward than using traditional methods. To read text files, you'll often use the same function, pd.read_csv(). However, to ensure the text file is read correctly, it's essential to use an additional parameter called sep, which stands for separator or delimiter in the text. Here's an example:

If your text file doesn't have a header row containing column names, set the header parameter to None. Doing so informs pandas not to treat the first row as column names.

Note

To specify a new line as the separator, use the code: sep='\r' where '\r' represents the carriage return.

Let's put this into practice!

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 2
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TXT Files

Text files are another common data format, and the pandas library makes it easy to work with them — often more straightforward than using traditional methods. To read text files, you'll often use the same function, pd.read_csv(). However, to ensure the text file is read correctly, it's essential to use an additional parameter called sep, which stands for separator or delimiter in the text. Here's an example:

If your text file doesn't have a header row containing column names, set the header parameter to None. Doing so informs pandas not to treat the first row as column names.

Note

To specify a new line as the separator, use the code: sep='\r' where '\r' represents the carriage return.

Let's put this into practice!

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 2. Chapter 2
toggle bottom row

TXT Files

Text files are another common data format, and the pandas library makes it easy to work with them — often more straightforward than using traditional methods. To read text files, you'll often use the same function, pd.read_csv(). However, to ensure the text file is read correctly, it's essential to use an additional parameter called sep, which stands for separator or delimiter in the text. Here's an example:

If your text file doesn't have a header row containing column names, set the header parameter to None. Doing so informs pandas not to treat the first row as column names.

Note

To specify a new line as the separator, use the code: sep='\r' where '\r' represents the carriage return.

Let's put this into practice!

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Text files are another common data format, and the pandas library makes it easy to work with them — often more straightforward than using traditional methods. To read text files, you'll often use the same function, pd.read_csv(). However, to ensure the text file is read correctly, it's essential to use an additional parameter called sep, which stands for separator or delimiter in the text. Here's an example:

If your text file doesn't have a header row containing column names, set the header parameter to None. Doing so informs pandas not to treat the first row as column names.

Note

To specify a new line as the separator, use the code: sep='\r' where '\r' represents the carriage return.

Let's put this into practice!

Task

  1. Read the TXT file into a DataFrame (use the link below as the first argument of the function).
  2. Display the output on your screen.

You can access the TXT file by clicking on the following link: Link to file

The actual link: https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a43d24b6-df61-4e11-9c90-5b36552b3437/pandas.txt

Switch to desktop for real-world practiceContinue from where you are using one of the options below
Section 2. Chapter 2
Switch to desktop for real-world practiceContinue from where you are using one of the options below
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