Vega-Altair Line Chart

Introduction

Vega-Altair package is a powerful tool for data visualization, particularly within Jupyter Notebooks. It has a wide range of charts and plots to explore and one of them is Line Chart. We've prepared several examples to demonstrate how Vega-Altair works:

simple line chart
line chart with pandas data
an interactive line chart

If you need any information about Vega-Altair check their docs: Vega-Altair Docs (opens in a new tab).

All of code examples are availabe as Jupyter Notebooks in our GitHub repositiory:

Line Chart

Visualization with only vega-altair package:

# import packages
import altair as alt 
 
# create data 
data = alt.Data(values=[{'x': 1, 'y': 5},
                        {'x': 2, 'y': 10},
                        {'x': 3, 'y': 6},
                        {'x': 4, 'y': 8},
                        {'x': 5, 'y': 3},
                        {'x': 6, 'y': 7},
                        {'x': 7, 'y': 9},
                        {'x': 8, 'y': 2},
                        {'x': 9, 'y': 4}])
 
# plot 
alt.Chart(data).mark_line().encode(
    x = 'x:N',
    y = 'y:Q'
).properties(
    width=500
)

Line Chart with Pandas Data

Using vega-altair, create a line chart with pandas data:

# import packages 
import altair as alt 
import pandas as pd 
 
# create data 
df = pd.DataFrame({
    'x': [1,2,3,4,5,6,7,8,9,10],
    'y': [6,20,9,5,20,2,10,5,14,1]
})
 
# plot 
alt.Chart(df).mark_line().encode(
    x = 'x',
    y = 'y'
).properties(
    width=500
)

Vega-altair line chart with pandas data.

Interactive Line Chart

Regular charts are not very exciting. What about creating an interactive line chart with vega-altair and mercury packages? You can decide if point will be visible using mercury widgets. In this example we used Checkbox (opens in a new tab).

# import packages
import altair as alt 
import mercury as mr 
import pandas as pd

# mercury widget
checkbox= mr.Checkbox(label="Points")

# create data 
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20],
    'y': [9,22,7,4,17,10,28,15,20,26,27,16,28,27,11,12,25,29,27,9]
})
point=alt.OverlayMarkDef(color="red") if checkbox.value else False
 
# plot 
alt.Chart(df).mark_line(
    point=point
).encode(
    x='x',
    y='y'
).properties(
    width=500
)

Now, you can easily convert your Jupyter Notebook into a Web App! Watch the video to see what it will look like.

Deploying Web App is very easy that you can do it in 3 steps:

Login to Mercury Cloud

If you don't have account, you can create it here: Mercury Cloud (opens in a new tab).

Create new site

Create new or use an existing site.

Upload your notebook

Upload the notebook with code.

Congrats! You just created your own Web App and you can share your Jupyter Notebooks with nontechnical users. If you need more information about deploying the Web App check Mercury Cloud Documentation (opens in a new tab).

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