pip install plotly

pip install notebook

import plotly.express as px
import plotly.graph_objects as go

import plotly.express as px

df = px.data.iris()

fig = px.scatter(df,
                 x="sepal_width",
                 y="sepal_length",
                 color="species")

fig.show()

import plotly.express as px

df = px.data.gapminder().query("country=='India'")

fig = px.line(df,
              x="year",
              y="lifeExp",
              title="Life Expectancy")

fig.show()

fig = px.scatter(df,
                 x="gdpPercap",
                 y="lifeExp",
                 color="continent",
                 size="pop")

fig = px.bar(df,
             x="year",
             y="pop"

fig = px.histogram(df,
                   x="lifeExp")

fig = px.box(df,
             x="continent",
             y="lifeExp")

fig = px.violin(df,
                x="continent",
                y="lifeExp")

fig = px.pie(df,
             names="continent",
             values="pop")

fig = px.area(df,
              x="year",
              y="pop")

fig = px.scatter(
    df,
    x="gdpPercap",
    y="lifeExp",
    size="pop",
    color="continent"
)

fig = px.sunburst(
    df,
    path=["continent", "country"],
    values="pop"
)

fig = px.treemap(
    df,
    path=["continent", "country"],
    values="pop"
)

data = dict(
    stage=["Visit","Signup","Purchase"],
    users=[1000,500,200]
)

fig = px.funnel(
    data,
    x="users",
    y="stage"
)

fig = px.density_heatmap(
    df,
    x="gdpPercap",
    y="lifeExp"
)

fig = px.density_contour(
    df,
    x="gdpPercap",
    y="lifeExp"
)

fig = px.choropleth(
    df,
    locations="iso_alpha",
    color="lifeExp"
)

fig = px.scatter_geo(
    df,
    locations="iso_alpha",
    size="pop"
)

import pandas as pd

data = pd.DataFrame({
    "Task":["A","B"],
    "Start":["2024-01-01","2024-03-01"],
    "Finish":["2024-02-01","2024-05-01"]
})

fig = px.timeline(
    data,
    x_start="Start",
    x_end="Finish",
    y="Task"
)

fig = px.line_polar(
    r=[1,2,3],
    theta=[0,90,180]
)

fig = go.Figure()

fig.add_trace(go.Scatterpolar(
    r=[5,4,3,4],
    theta=['Math','Physics','Chemistry','English'],
    fill='toself'
))

fig.show()

fig = px.scatter_3d(
    df,
    x="gdpPercap",
    y="lifeExp",
    z="pop"
)

fig = px.line_3d(
    df,
    x="year",
    y="lifeExp",
    z="pop"
)

import numpy as np

z = np.random.rand(10,10)

fig = go.Figure(
    data=[go.Surface(z=z)]
)

fig = go.Figure(
    data=[go.Mesh3d(
        x=[0,1,2],
        y=[0,1,0],
        z=[0,1,2]
    )]
)

import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(
    go.Bar(
        x=["A","B","C"],
        y=[10,20,30]
    )
)

fig.show()

fig.update_layout(
    title="Sales Report",
    xaxis_title="Month",
    yaxis_title="Sales",
    template="plotly_dark"
)

template="plotly"

template="plotly_dark"

template="ggplot2"

template="seaborn"

template="simple_white"

fig = go.Figure()

fig.add_trace(
    go.Scatter(
        x=[1,2,3],
        y=[4,5,6]
    )
)

fig.add_trace(
    go.Scatter(
        x=[1,2,3],
        y=[6,5,4]
    )
)

from plotly.subplots import make_subplots

fig = make_subplots(
    rows=1,
    cols=2
)

fig.add_trace(
    go.Bar(
        x=[1,2],
        y=[3,4]
    ),
    row=1,
    col=1
)

fig.show()

fig.update_traces(
    marker_color="red",
    marker_size=12
)

fig.update_xaxes(title="Year")

fig.update_yaxes(title="Population")

fig.update_traces(
    hovertemplate="%{x}<br>%{y}"
)

fig.add_annotation(
    x=2,
    y=5,
    text="Peak"
)

fig.add_shape(
    type="rect",
    x0=1,
    y0=2,
    x1=3,
    y1=5
)

fig.add_shape(
    type="line",
    x0=0,
    y0=0,
    x1=5,
    y1=5
)

fig = px.scatter(
    df,
    x="gdpPercap",
    y="lifeExp",
    animation_frame="year"
)

fig.write_html("graph.html")

fig.write_image("graph.png")

fig.show()