Tutorial

PyG2 is very logical and commnds are simple when it comes to graphic generations.

  • Installation:

    pip install pyG2

  • Open Jupyter Notebook

  • Import modules:

    from pyG2 import G2
import pandas as pd

  • In this example we use mtcars dataset from https://vincentarelbundock.github.io/Rdatasets/csv/datasets/mtcars.csv Download CSV file, save it in the same folder as the notebook and change the header of the first column to name

  • Prepare a Panda DataFrame:

    df = pd.read_csv('mtcars.csv')
Columns are ‘name’, ‘mpg’, ‘cyl’, ‘disp’, ‘hp’, ‘drat’, ‘wt’, ‘qsec’, ‘vs’, ‘am’,
‘gear’ and ‘carb’.

Data preperation

Data should be processed by panda dataframe if any transformation presents.

Chart Layout Configuration

We have to construct a graph object:

chart = G2.Chart(height, width, autoFit, limitInPlot, padding, pixelRatio, renderer, visible)

All parameters are optional.

height: int (ppt) (default 500)

width: int (ppt) (default 400)

autoFit: ‘true’ / ‘false’ (default ‘true’) ‘true’ (str) not True (bool)

limitInPlot: ‘true’ / ‘false’ (default ‘false’)

padding: int/ [int,int,int,int]

pixelRatio: int (pixelRatio for canvas rendering)

render: ‘canvas’/’svg’

visible: ‘true’/’false’

  • Display changes:

    chart.render()

All other codes comes between Chart object construction and rendering steps.

Variable Maps

One dimension map: e.g. name Two dimensional variable map: e.g name*cyl