Data

Data types

ipyvizzu currently supports two types of data series: dimensions and measures. Dimensions slice the data cube ipyvizzu uses, whereas measures are values within the cube.

Dimensions are categorical series that can contain strings and numbers, but both will be treated as strings. Temporal data such as dates or timestamps should also be added as dimensions. By default, ipyvizzu will draw the elements on the chart in the order they are provided in the data set. Thus we suggest adding temporal data in a sorted format from oldest to newest.

Measures at the moment can only be numerical.

Adding data

There are multiple ways you can add data to ipyvizzu.

• Using pandas DataFrame
• Specify data by series - column after column if you think of a spreadsheet
• Specify data by records - row after row
• Using data cube form
• Using JSON

Tip

You should set the data in the first animate call.

chart.animate(data)

Using pandas DataFrame

Use add_data_frame method for adding data frame to Data.

music_data.csv:

Genres,Kinds,Popularity
Pop,Hard,114
Rock,Hard,96
Jazz,Hard,78
Metal,Hard,52
Pop,Smooth,56
Rock,Smooth,36
Jazz,Smooth,174
Metal,Smooth,121
Pop,Experimental,127
Rock,Experimental,83
Jazz,Experimental,94
Metal,Experimental,58

import pandas as pd
from ipyvizzu import Data


data_frame = pd.read_csv(
    "https://ipyvizzu.vizzuhq.com/0.14/assets/data/music_data.csv"
)

data = Data()
data.add_data_frame(data_frame)

Info

ipyvizzu makes a difference between two types of data, numeric (measure) and not numeric (dimension). A column's dtype specifies that the column is handled as a measure or as a dimension.

It is also possible to add data frame index to Data with the add_data_frame_index method.

import pandas as pd
from ipyvizzu import Data


data_frame = pd.DataFrame(
    {"Popularity": [114, 96, 78]}, index=["x", "y", "z"]
)

data = Data()
data.add_data_frame(data_frame)
data.add_data_frame_index(data_frame, "DataFrameIndex")

Specify data by series

When you specify the data by series or by records, it has to be in first normal form. Here is an example of that:

Genres	Kinds	Popularity
Pop	Hard	114
Rock	Hard	96
Jazz	Hard	78
Metal	Hard	52
Pop	Smooth	56
Rock	Smooth	36
Jazz	Smooth	174
Metal	Smooth	121
Pop	Experimental	127
Rock	Experimental	83
Jazz	Experimental	94
Metal	Experimental	58

from ipyvizzu import Data


data = Data()
data.add_series(
    "Genres",
    [
        "Pop",
        "Rock",
        "Jazz",
        "Metal",
        "Pop",
        "Rock",
        "Jazz",
        "Metal",
        "Pop",
        "Rock",
        "Jazz",
        "Metal",
    ],
    type="dimension",
)
data.add_series(
    "Kinds",
    [
        "Hard",
        "Hard",
        "Hard",
        "Hard",
        "Smooth",
        "Smooth",
        "Smooth",
        "Smooth",
        "Experimental",
        "Experimental",
        "Experimental",
        "Experimental",
    ],
    type="dimension",
)
data.add_series(
    "Popularity",
    [114, 96, 78, 52, 56, 36, 174, 121, 127, 83, 94, 58],
    type="measure",
)

Specify data by records

from ipyvizzu import Data


data = Data()

data.add_series("Genres", type="dimension")
data.add_series("Kinds", type="dimension")
data.add_series("Popularity", type="measure")

record = ["Pop", "Hard", 114]

data.add_record(record)

records = [
    ["Rock", "Hard", 96],
    ["Jazz", "Hard", 78],
    ["Metal", "Hard", 52],
    ["Pop", "Smooth", 56],
    ["Rock", "Smooth", 36],
    ["Jazz", "Smooth", 174],
    ["Metal", "Smooth", 121],
    ["Pop", "Experimental", 127],
    ["Rock", "Experimental", 83],
    ["Jazz", "Experimental", 94],
    ["Metal", "Experimental", 58],
]

data.add_records(records)

Using data cube form

		Genres
		Pop	Rock	Jazz	Metal
Kinds	Hard	114	96	78	52
	Smooth	56	36	74	121
	Experimental	127	83	94	58
		Popularity

from ipyvizzu import Data


data = Data()

data.add_dimension("Genres", ["Pop", "Rock", "Jazz", "Metal"])
data.add_dimension("Kinds", ["Hard", "Smooth", "Experimental"])

data.add_measure(
    "Popularity",
    [
        [114, 96, 78, 52],
        [56, 36, 174, 121],
        [127, 83, 94, 58],
    ],
)

Using JSON

music_data.json (in this example the data stored in the data cube form):

{
  "dimensions": [
    {
      "name": "Genres",
      "values": [
        "Pop",
        "Rock",
        "Jazz",
        "Metal"
      ]
    },
    {
      "name": "Kinds",
      "values": [
        "Hard",
        "Smooth",
        "Experimental"
      ]
    }
  ],
  "measures": [
    {
      "name": "Popularity",
      "values": [
        [
          114,
          96,
          78,
          52
        ],
        [
          56,
          36,
          174,
          121
        ],
        [
          127,
          83,
          94,
          58
        ]
      ]
    }
  ]
}

from ipyvizzu import Data


data = Data.from_json("../assets/data/music_data.json")