2. File

Read or Write a File

1. In the Data Analysis category, click File.

2. Select the type of action Read File / Write File

   1. Sample Data brings up sample data provided by Visual Python.

Read File

1. File Type: Select the type of file you want to import.

2. File Path: The file-shaped icon lets you find the location of the file to load.

3. Allocate to: Give the file a variable name.

• Additional Options: Allows you to set additional option values. If not set, the default values set in Visual Python are applied. Options not listed here can be applied by entering them directly in User Option.

1. Encoding: Select the type of encoding.

2. Header: By default, the first row is used as the column name. If you don't want this, select 'None'.

3. Separator: Choose a separator to separate the data fields in the file.

4. Columns: Set the column names to a pre-made list or specific values.

5. Column List to Use: Allows you to import only specific columns within the file.

6. Column to Use as Index: Specify which column in the data should be used as the index.

7. Na Values: Replace missing values with the values you entered.

8. Rows to Skip: Skips and fetches as many rows as the value entered at the top of the file.

9. Number of Rows: Fetches as many rows as the entered value from the top of the file.

10. Chunksize: Reads the file in chunks, divided by the entered value. Use this when loading large files.

Write File

1. File Type: Set the file type you want to save.

2. DataFrame: Select the dataframe you want to save.

3. File Path: Set the location where you want to save the file.

• Additional Options: Allows you to set additional option values. If not set, the default values set in Visual Python are applied. Options not listed here can be applied by entering them directly in User Option.

1. Encoding: Select the type of encoding.

2. Header: Select 'False' if you do not want the column names to be included in the file that will be saved.

3. Index: Select 'False' if you don't want an index to be included.

4. Separator: Choose a separator to separate the data fields in the file.

5. Na Replacing Value: Replaces the missing value with the value you entered.

6. Columns: Select specific columns to save.