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Yandex DataLens
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  1. Visualization reference
  2. Normalized bar chart

Normalized bar chart

Written by
Yandex Cloud
,
improved by
Dmitry A.
  • Sections in the wizard
  • Creating a normalized bar chart
  • Recommendations

A normalized bar chart shows the contribution, as a percentage, of multiple measures in the total amount by period or category. Unlike a stacked bar chart, the proportion of segment ratios and not the total bar length is important for this type of chart. Segments are highlighted in different colors and located one after the other. The length of a segment indicates its ratio to the total amount represented as 100%. For example, the percentage of expenses in the annual budget.

normalized-horizontal-bar-chart

Source table
Month Gasoline Rent Food Utility bills
January 2019 100 600 300 500
February 2019 150 600 250 700
March 2019 100 600 450 400
April 2019 120 600 370 510
May 2019 100 600 300 530
June 2019 130 600 310 600
July 2019 150 600 330 510
August 2019 120 600 250 550
September 2019 110 650 380 500
October 2019 120 650 300 550
November 2019 130 650 310 540
December 2019 100 650 400 550

Or the percentage distribution of payment types across product subcategories.

normalized-horizontal-bar-chart-categories

Source table
Subcategory Delivery Pickup
Beauty and health products 615K 373K
Kitchenware 1929K 1005K
Kitchen products 1217K 759K
Detergents 1210K 803K
Health and beauty equipment 2046K 1380K
Non-essential goods 1368K 894K
Cleaners 1237K 673K

A normalized bar chart shows the contribution, as a percentage, of each category in the total measure value over a time interval. For example, the percentage of sales for different product categories.

normalized-horizontal-bar-chart-2

Source table
Month Home appliances Household goods Household cleaners
January 2019 128K 55K 26K
February 2019 97K 79K 18K
March 2019 187K 105K 41K
April 2019 188K 137K 34K
May 2019 230K 121K 43K
June 2019 256K 162K 59K
July 2019 284K 206K 67K
August 2019 409K 204K 72K
September 2019 314K 209K 86K
October 2019 324K 262K 79K
November 2019 385K 238K 101K
December 2019 451K 307K 111K

Sections in the wizard

Section
in the wizard
Description
Y Dimensions. One or two dimensions can be specified. For the Date and Date and time types, you can set grouping by time: minutes, hours, weeks, and so on.
X Measure. You can specify multiple measures. If you add more than one measure to a section, the Colors section contains a dimension named Measure Names. You may move Measure Names to the Y-axis.
Colors Dimension or the Measure Names field. Affects the color of lines. Measure Names is removed by deleting measures from the Y-axis.
Sorting Dimension or measure. Affects the sorting of columns.
Signatures Measure. Displays measure values on the chart. If multiple measures are added to the Y section, drag Measure Values to this section.
Chart filters Dimension or measure. Used as a filter.

Creating a normalized bar chart

To create a normalized bar chart:

  1. On the Yandex DataLens home page, click Create chart.
  2. Under Dataset, select a dataset for visualization.
  3. Select Normalized bar chart as the chart type.
  4. Drag one or more dimensions from the dataset to the Y section. The values are displayed on the Y-axis.
  5. Drag one or more measures from the dataset to the X section.
  6. Drag a dimension from the dataset or the Measure Names field to the Colors section.

Recommendations

  • If the values of the categories contain a large amount of text, try to reduce it. Then the signatures on the diagram will look more accurate. You can use string functions in the calculated fields or conditional operators CASE.

  • Don't display more than 3-5 segments on the chart.
  • When visualizing multiple measures, select colors carefully. They should be distinguishable and contrasting. We recommend using no more than 3-5 colors per chart. If you want to emphasize one certain measure above the others, highlight it in some bright color.

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© 2023 Yandex.Cloud LLC
In this article:
  • Sections in the wizard
  • Creating a normalized bar chart
  • Recommendations