Aggregating data

The default logic of ipyvizzu is to show the sum of values that are in the categories added to a chart. So if we create a simple vertical bar chart by adding the Popularity measure to the y-axis, the height of the bar will be the sum of all Popularity values and when we add Genres to the x-axis, the height of the bars will be the sum of Popularity values in each category within Genres.

Info - How to setup Chart

import pandas as pd
from ipyvizzu import Chart, Data, Config

df = pd.read_csv(
    "https://ipyvizzu.vizzuhq.com/0.16/assets/data/music_data.csv"
)
data = Data()
data.add_df(df)

chart = Chart()

chart.animate(data)

chart.animate(Config({"channels": {"y": {"set": ["Popularity"]}}}))

chart.animate(Config({"channels": {"x": {"set": ["Genres"]}}}))

Next to the default logic of sum, there are a handful of other aggregation logics that are available in ipyvizzu: min, max, mean, count and distinct. Let's go through them to see how they work.

Minimum value: the height of the bars show the minimum value in the Popularity measure in each of the Genres.

chart.animate(
    Config({
        "channels": {
            "y": {
                "set": ["min(Popularity)"]
            }
        }
    })
)

Maximum value: the height of the bars show the maximum value in the Popularity measure in each of the Genres.

chart.animate(
    Config({
        "channels": {
            "y": {
                "set": ["max(Popularity)"]
            }
        }
    })
)

Mean value: the height of the bars show the mean value of the Popularity measure in each of the Genres.

chart.animate(
    Config({
        "channels": {
            "y": {
                "set": ["mean(Popularity)"]
            }
        }
    })
)

Count: the height of the bars show the number of items (rows if you will) in each of the Genres.

chart.animate(
    Config({
        "channels": {
            "y": {
                "set": ["count()"]
            }
        }
    })
)

Distinct: the height of the bars show the number of distinct categories of Kinds in each of the Genres.

Note

Distinct aggregation logic relates to dimensions like Genres and not to measures like Popularity.

chart.animate(
    Config({
        "channels": {
            "y": {
                "set": ["distinct(Kinds)"]
            }
        }
    })
)

Sum: this is how you can get back to the default aggregation logic of ipyvizzu that sums the Popularity values in each of the Genres.

chart.animate(
        Config({
            "channels": {
                "y": {
                    "set": ["sum(Popularity)"]
                }
            }
        })