---
title: Read data from CSV
slug: how-tos/QJcp-read-data-from-csv
createdAt: 2025-09-02T09:24:57.907Z
---

## Introduction to CSV

### What?

CSV (Comma-Separated Values) is a simple file format used to store tabular data, such as measurements or sensor readings. Each line in the file represents a row, and each value is separated by a delimiter (commonly a comma).

### Why?

- **Compatibility with existing systems:** Most data exporters, sensors, and logging tools support CSV.
- **Broad usage:** Easy to read, process, and share across platforms and programming languages.

## CSV settings

The Measurement Settings section configures how CSV data is interpreted and mapped into measurements. This includes defining how each column in the CSV file is used, setting up filters for data inclusion, and specifying data quality indicators.

### ValueColumn

**Description**: Column of the value in the csv file for this measurement.
**Required**: yes
**Example**: 6

### StatusGood

**Description**: All values that are mapped to status 'Good'. Multiple statuses can be configured using semicolon separated values.
**Required**: no
**Example**: "Valid;correct"

### TimestampLayout

**Description**: The layout of the timestamp, defaults to the TimestampLayout setting on the collector. More info: [https://pkg.go.dev/time#Layout\\](https://pkg.go.dev/time#Layout\\)
**Required**: no

### TagsInCSV

**Description**:This allows to add tags to the measurement with the tag value coming from csv data. The structure of this setting is similar as the `Filter` setting. The json key is the column index (as string) where the tag value is present, and the json value is the tag key (or tag name) under which the data should be stored upon the measurement:
**Required**: no
**Example**:`{"4": "Description"}`

### FilterByRegularExpression

**Description**: If true, values in Filter will be treated as a regular expression. If false, values in Filter will be treated as a (list of) value to match. Default is false.
**Required**: no

### Locale

**Description**: The locale with which numbers should be parsed. Default is the value of the corresponding setting on the collector.
**Required**: no

This table lists some examples of number formats and the locale with which they can be correctly parsed to a number the collector can process.
The output in these examples is always the same: 1234.56

| input    | locale |
| -------- | ------ |
| 1 234.56 | en-GB  |
| 1,234.56 | en-US  |
| 1.234,56 | de-DE  |
| 1 234,56 | fr-FR  |
| 1234,56  | nl-BE  |

### Read CSV data

### Use JSON settings

Filters can be configured via JSON:

### Filter

**Description**: Filter to parse only the rows that match the filter. The filter is a JSON object where the key is the column index (as a string) and the value is an exact value to match. To match against a set of exact values, separate them with a semicolon. To use the value as a regular expression, set FilterByRegularExpression to true. Backslashes in regulars expressions need to be escaped with another backslash. Use \{} to leave empty.
**Required**: no
**Details**:

- **Key**: CSV column index as a string.
- **Value**: Names used for mapping, separated by semicolons if multiple.

**Example**:
In the following example (with `FilterByRegularExpression` set to `false`), the filter will only parse rows where the value of the first column is `Example value` and the value of the second column is `match with this` or `also match with this`.

```json
{
  "0": "Example value",
  "1": "match with this;also match with this"
}
```

In the following example (with `FilterByRegularExpression` set to `true`), the filter will only parse rows where the value of the first column contains `Example` and the value of the second column is `match with this` or `also match with this`.

```json
{
  "0": "Example",
  "1": "^(match with this|also match with this)$"
}
```

## Examples

### Example 1

Given the following CSV format, with files being provided by a data source located in \`Europe/Brussels\`.

```csv
Time,Name,Value,Unit,Quality
"1/12/2023 13:00:01.868",P99,"0.00",,Good
"1/12/2023 13:01:01.876",P99,"0.00",,Good
"1/12/2023 13:02:01.863",P99,"100.00",,Good
"1/12/2023 13:03:01.840",P99,"100.00",,Good
"1/12/2023 13:00:01.868",TT100,"27.51",,Good
"1/12/2023 13:01:01.876",TT100,"26.04",,Good
"1/12/2023 13:02:01.863",TT100,"25.97",,Good
"1/12/2023 13:03:01.840",TT100,"26.23",,Good

```

Settings of the collector and the measurement would be configured as below:

**Collector settings:**

| Setting         | Value                  |
| --------------- | ---------------------- |
| Delimiter       | ,                      |
| CSVHeader       | true                   |
| TimestampColumn | 0                      |
| TimestampLayout | 2/01/2006 15:04:05.000 |
| StatusColumn    | 4                      |
| TrimString      | *No Value*             |

| Advanced Setting | Value             |
| ---------------- | ----------------- |
| SourceTimezone   | `Europe/Brussels` |

**Measurement settings:**

| Setting         | Value           |
| --------------- | --------------- |
| Name            | Area\_Pump99    |
| ValueColumn     | 2               |
| Filter          | \{ "1": "P99" } |
| StatusGood      | Good            |
| TagsInCSV       | \{}             |
| TimestampLayout | *No Value*      |

| Setting         | Value                |
| --------------- | -------------------- |
| Name            | Area\_Temperature100 |
| ValueColumn     | 2                    |
| Filter          | \{ "1": "TT100" }    |
| StatusGood      | Good                 |
| TagsInCSV       | \{}                  |
| TimestampLayout | *No Value*           |

## Troubleshooting

### Incorrect value parsing

Check `Locale` and number format.

### Timestamp errors

Check `TimestampLayout` and confirm it is correct.