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On this page
  • Overview
  • Column type
  • Dates
  • Decimals
  • Separators

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  1. Data Management
  2. Datasources in Toucan
  3. Managing Files

Using advanced file settings

Last updated 1 year ago

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Overview

We all want to drop a file in Toucan (excel, CSV…) and directly use it in our charts! Most of the time, the file appears perfectly fine on Toucan.

However, let me show you some very useful tricks and directives that will help you if your datasource doesn’t appear properly in the tool.

Sometimes, even when you applied all the requirements for a good flat file as expected by Toucan, you might need to customize the data interpretation done by Toucan to transform a datasource into a dataset.

Column type

The first tip to remember for both Excel and CSV files is that in Toucan, numbers appear in blue, and the strings are in black. When loading a file, some numbers might not be recognized as numbers, for instance.

It is never too late! You can easily pick your datasource in the data explorer and previsualize it.

You have 2 different ways to do it:

  • With the visual interface (in the "CONVERT VALUES" field): you can add your dtype parameter, please write it in a JSON format. For example: { "labels": "str" }

  • With the code mode interface: you can use the function dtype, followed by the name of the column and by the type. For example: dtype: labels : 'str'

Dates

For some file types, like Excel or Google Sheets, Toucan should understand that some columns contain dates. But for others, like CSVs, there is no way to find out automatically.

No worries, it’s super easy to tell Toucan which column to parse as a date: just tick the box “parse columns as dates” and indicate the names of dates columns.

Decimals

For CSV files: another quite tricky situation is when your file is formatted with decimal separators like the comma (,) instead of the international standard (the dot .).

But again, no problem for Toucan; you have two different ways to indicate it:

  • With the visual interface: you can add your decimal parameter, in the "DECIMAL" field. Just write the desired character.

  • With the code mode interface: you can use the function decimal, followed by the character. For example: decimal: ","

Separators

For CSV files: Last trick here concerns the format of the file. As it’s very common in CSV files.

We all know that sometimes when we open our CSV file, all the data is not separated into different columns, and you need to apply your separator directly in Excel. This also happens in Toucan. No worries, I got a solution 🙏

You have two different ways to do it:

  • With the visual interface: you can add your separator parameter, in the "SEP" field. Just write the desired character.

  • With the code mode interface: you can use the function sep, followed by the character. For example: sep: ","

💡 Note that these options come from the panda's library we use to interpret the files. If you want to check all the options available, you can find them under the following links:

Let’s go!

for CSV:

for excel:

📡
📁
📂
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html