Yandex Cloud
  • Services
  • Solutions
  • Why Yandex Cloud
  • Pricing
  • Documentation
  • Contact us
Get started
Language / Region
© 2022 Yandex.Cloud LLC
Yandex DataLens
  • Getting started
  • Practical guidelines
    • All tutorials
    • Visualizing data from a CSV file
    • Creating and publishing a chart with a map of Moscow from a CSV file
    • Analyzing a retail chain's sales from a ClickHouse database
    • Analyzing public data on road accidents in Russia
    • Analyzing sales and locations of pizzerias based on data from Clickhouse DB and Marketplace
    • Web analytics with a connection to Yandex Metrica
    • Web analytics with funnels and cohorts calculated based on Yandex Metrica data
    • Mobile app analytics based on AppMetrica data
    • Analyzing Yandex Music podcast statistics (for podcasters)
    • Visualizing data with a QL chart
    • Building customer journey charts based on AppMetrica data
  • Concepts
    • Service overview
    • Connection
    • Data types
    • Datasets
      • Overview
      • Data model
      • Dataset settings
    • Charts
      • Overview
      • Chart types
      • Chart settings
    • Dashboards
    • Combining data
    • Using Markdown in DataLens
    • DataLens Public
    • Aggregations in DataLens
    • Calculated fields
      • Overview
      • Formula syntax
    • Parameterization
    • Marketplace
    • Backups
    • Caching
    • Quotas and limits
    • Organizations in DataLens
  • Step-by-step instructions
    • All instructions
    • Working with connections
      • Creating a ClickHouse connection
      • Creating a connection to a CSV file
      • Creating a Google Sheets connection
      • Creating a MySQL connection
      • Creating a PostgreSQL connection
      • Creating an MS SQL Server connection
      • Creating an Oracle Database connection
      • Creating a YDB connection
      • Creating a Yandex Metrica API connection
      • Creating an AppMetrica connection
      • Creating a Yandex Cloud Billing connection
      • Creating a Greenplum connection
      • Managing connection access
    • Working with datasets
      • Creating a dataset
      • Combining data from multiple tables
      • Combining data from multiple CSV connections
      • Creating a data field
      • Creating a calculated data field
      • Creating a default filter for new charts
      • Updating fields in datasets
      • Describing a dataset via a source SQL query
      • Dataset materialization
      • Managing dataset access
      • Managing access to data rows
      • Adding parameters to a dataset
    • Working with charts
      • Creating a line chart
      • Creating an area chart
      • Creating a pie chart
      • Creating a donut chart
      • Creating a column chart
      • Creating a bar chart
      • Creating a scatter chart
      • Creating a map
      • Creating a table
      • Creating a pivot table
      • Creating an indicator
      • Creating a tree chart
      • Creating a QL chart
      • Creating a multi-dataset chart
      • Adding a hierarchy
      • Configuring the navigator
      • Publishing a chart
      • Managing chart access
      • Adding guid as a parameter
      • Adding parameters to a chart
    • Working with dashboards
      • Creating dashboards
      • Adding charts to dashboards
      • Adding selectors to dashboards
      • Creating an alias
      • Deleting an alias field
      • Publishing dashboards
      • Managing dashboard access
      • Dashboard auto-update
    • Working with permissions
      • Granting permissions
      • Deleting permissions
      • Request permissions
    • Working with DataLens Marketplace
      • Adding a product from Marketplace
      • Removing a product from Marketplace
      • Creating and using a connector (for partners)
    • Working with organizations
      • Switching between DataLens instances
  • Access management
    • Managing access to DataLens
    • Managing access at the data row level
  • Pricing policy
  • Function reference
    • All Functions
    • Aggregate functions
      • Overview
      • ALL_CONCAT
      • ANY
      • ARG_MAX
      • ARG_MIN
      • AVG
      • AVG_IF
      • COUNT
      • COUNTD
      • COUNTD_APPROX
      • COUNTD_IF
      • COUNT_IF
      • MAX
      • MEDIAN
      • MIN
      • QUANTILE
      • QUANTILE_APPROX
      • STDEV
      • STDEVP
      • SUM
      • SUM_IF
      • TOP_CONCAT
      • VAR
      • VARP
    • Array functions
      • Overview
      • ARRAY
      • ARR_AVG
      • ARR_MAX
      • ARR_MIN
      • ARR_PRODUCT
      • ARR_STR
      • ARR_SUM
      • CAST_ARR_FLOAT
      • CAST_ARR_INT
      • CAST_ARR_STR
      • CONTAINS
      • COUNT_ITEM
      • GET_ITEM
      • REPLACE
      • SLICE
      • STARTSWITH
      • UNNEST
    • Date/Time functions
      • Overview
      • DATEADD
      • DATEPART
      • DATETRUNC
      • DAY
      • DAYOFWEEK
      • HOUR
      • MINUTE
      • MONTH
      • NOW
      • QUARTER
      • SECOND
      • TODAY
      • WEEK
      • YEAR
    • Geographical functions
      • Overview
      • GEOCODE
      • GEOINFO
      • TOPONYM_TO_GEOPOINT
      • TOPONYM_TO_GEOPOLYGON
    • Logical functions
      • Overview
      • CASE
      • IF
      • IFNULL
      • ISNULL
      • ZN
    • Mathematical functions
      • Overview
      • ABS
      • ACOS
      • ASIN
      • ATAN
      • ATAN2
      • CEILING
      • COMPARE
      • COS
      • COT
      • DEGREES
      • DIV
      • EXP
      • FLOOR
      • GREATEST
      • LEAST
      • LN
      • LOG
      • LOG10
      • PI
      • POWER
      • RADIANS
      • ROUND
      • SIGN
      • SIN
      • SQRT
      • SQUARE
      • TAN
    • Operators
      • Overview
      • AND
      • Addition and concatenation (+)
      • BETWEEN
      • Comparison
      • Division (/)
      • IN
      • IS FALSE
      • IS TRUE
      • LIKE
      • Modulo (%)
      • Multiplication (*)
      • NOT
      • Negation (-)
      • OR
      • Power (^)
      • Subtraction (-)
    • String functions
      • Overview
      • ASCII
      • CHAR
      • CONCAT
      • CONTAINS
      • ENDSWITH
      • FIND
      • ICONTAINS
      • IENDSWITH
      • ISTARTSWITH
      • LEFT
      • LEN
      • LOWER
      • LTRIM
      • REGEXP_EXTRACT
      • REGEXP_EXTRACT_NTH
      • REGEXP_MATCH
      • REGEXP_REPLACE
      • REPLACE
      • RIGHT
      • RTRIM
      • SPACE
      • SPLIT
      • STARTSWITH
      • SUBSTR
      • TRIM
      • UPPER
      • UTF8
    • Text markup functions
      • Overview
      • BOLD
      • ITALIC
      • MARKUP
      • URL
    • Time series functions
      • Overview
      • AGO
      • AT_DATE
    • Type conversion functions
      • Overview
      • BOOL
      • DATE
      • DATETIME
      • DATETIME_PARSE
      • DATE_PARSE
      • DB_CAST
      • FLOAT
      • GEOPOINT
      • GEOPOLYGON
      • INT
      • STR
    • Window functions
      • Overview
      • AVG
      • AVG_IF
      • COUNT
      • COUNT_IF
      • FIRST
      • LAG
      • LAST
      • MAVG
      • MAX
      • MCOUNT
      • MIN
      • MMAX
      • MMIN
      • MSUM
      • RANK
      • RANK_DENSE
      • RANK_PERCENTILE
      • RANK_UNIQUE
      • RAVG
      • RCOUNT
      • RMAX
      • RMIN
      • RSUM
      • SUM
      • SUM_IF
    • Function Availability
  • Tutorial on functions
    • Aggregate functions
    • Window functions
    • LOD expressions and filtering in aggregate functions
  • Public materials
    • Educational projects
    • Webinars and conferences
    • Articles and publications
    • Public dashboards and charts
  • Troubleshooting
    • Questions and answers
    • DataLens errors
  1. Concepts
  2. Charts
  3. Overview

Charts

Written by
Yandex Cloud
  • Dataset-based charts
    • Multi-dataset charts
  • QL charts
  • Publishing a chart
  • Access management

Charts are the visualization of data from a dataset in the form of a table, diagram, or map.

DataLens includes two types of charts:

  • Dataset-based charts
  • QL charts

Dataset-based charts

Charts are created in a wizard based on data from one or multiple datasets (see multi-dataset charts).
You can create an unlimited number of charts based on a single dataset.

The workspace in the wizard interface is divided into three main panels:

  1. A dataset panel where available fields are displayed: Dimensions and Measures. You can add a calculated field to the list.
  2. A visualization setup panel that you can use to select a chart type. Each type has its own set of sections (such as X-axis, Y-axis, and filters) where you can drag and drop fields. Learn more in Chart settings.
  3. A preview panel where the visualization is displayed.

Charts let you quickly analyze and test hypotheses. You can also save charts and add them to dashboards as widgets.

Warning

DataLens limits the number of data rows displayed in charts. Read about them in the section Quotas and limits.

Multi-dataset charts

Multi-dataset charts display data from multiple datasets.

Queries for each dataset are processed independently of each other. You cannot create calculated fields from fields in multiple datasets.
When you add a second dataset DataLens, the link is automatically created based on the first match for the field name and field data type.

In this case, you can:

  • Change links.
  • Add new links.
  • Delete links.

Note

Datasets used in the chart may be non-linked.

Specifics of working with linked datasets in the chart, except for geochart layers:

  • One chart can use any measures from datasets, regardless of their links.
  • One chart can only use linked dimensions.
  • Filters by linked dimensions are applied to all datasets.
  • Filters by non-linked dimensions are applied only to their own dataset.

Working with linked datasets in geovisualizations on different layers:

  • A geolayer can use any measures from datasets regardless of their links
  • A geolayer can only use its linked dimensions.
  • Filters by linked dimensions from the General filters section are applied to all datasets in all layers.
  • Filters from the General filters section that use non-linked dimensions only apply to their own dataset in all layers.
  • Filters in the Layer filters section that use linked dimensions apply to all datasets within the current layer.
  • Filters in the Layer filters section that use non-linked dimensions only apply to their own dataset within the current layer.
  • There are no restrictions on using non-linked dimensions in different layers.

QL charts

QL charts are charts created from a connection if the connection target is a database. Use a SQL query to build these charts. The query is executed using the original database's SQL flavor, which helps expand visualization capabilities by using database-specific transactions.

Executing a SQL query does not set up a separate Dataset object, but rather generates one on the fly and displays it in the preview panel.

Unlike regular charts, the logic of using the wizard in QL charts favors the SQL query, that is, the wizard only displays data from a query.

QL chart features:

  • They reduce database workload by using direct queries.
  • They are only suitable for SELECTs.
  • They enable the use of the JOIN, GROUP BY, and SORT BY operators as well as aggregate functions in a SQL query.
  • They enable the parameterization of any part of a SQL query.
  • They support a limited set of visualizations types.
  • They have public access restrictions.
  • They do not support data materialization.
  • They do not use RLS or calculated fields.
Query example for a ClickHouse database
SELECT Category, Month, ROUND(SUM(Sales))
FROM samples.SampleLite
WHERE Category in {{category}} -- a variable used in the selector
GROUP BY Category, Month -- grouping by category and month
ORDER BY Category, Month -- sorting by category and month

To create a QL chart, see the instructions.

Publishing a chart

You can grant any internet user access to a chart using DataLens Public. This chart becomes public and any user can view it without authorization.

To grant public access to a chart:

Warning

Before publishing any data, make sure that your charts and dashboards don't contain any personal data or trade secrets. Access to published data is not restricted.

  1. On the navigation page, find the chart and open it.

  2. At the top of the wizard interface, click .

  3. In the window that opens, enable Access via link. DataLens automatically grants access to related objects.

    Warning

    You should materialize the dataset that the object is based on.

    If the data source is a ClickHouse DB in Yandex Cloud, then materialization is not required.

  4. Copy the public link and click Apply.

Access management

You can configure chart permissions.

To configure chart permissions:

  1. On the navigation page, find the chart that you want to change permissions for.
  2. On the right side, click and select Configure access.
  3. Enter the username in the Add participants field and click Select.
  4. In the window that opens, select the permission type and click Add.

For more information about types of permissions, see Managing access to DataLens.

See also

  • Creating a line chart
  • Creating a pivot table
  • Creating a table
  • Creating an stacked area chart
  • Creating a column chart
  • Creating a bar chart
  • Creating a pie chart
  • Creating a map
  • Creating a QL chart
  • Publishing a chart

Was the article helpful?

Language / Region
© 2022 Yandex.Cloud LLC
In this article:
  • Dataset-based charts
  • Multi-dataset charts
  • QL charts
  • Publishing a chart
  • Access management