import plotly.graph_objects as go

funnel_fig = go.Figure()
funnel_fig.add_trace(
    go.Funnel(
        name="商品1",
        x=[350, 170, 25, 12],
        y=["閲覧", "クリック", "カートに追加", "購入"],
        textinfo="percent initial"  		# 百分率を表示し、初期値からの変化で描画
    )
)
funnel_fig.add_trace(
    go.Funnel(
        name="商品2",
        orientation="h",
        x=[210, 45, 17, 10],
        y=["閲覧", "クリック", "カートに追加", "購入"],
        textinfo="label+percent previous"  # ラベルと百分率を表示し、前の値からの変化で描画
    )
)
funnel_fig.show()

import plotly.graph_objects as go

go.Figure(
    go.Waterfall(
        x=[
            "売上高",
            "売上原価",
            "売上総利益",
            "販売費及び一般管理費",
            "営業利益",
            "営業外収益",
            "営業外費用",
            "経常利益",
            "特別利益",
            "特別損失",
            "税引前当期純利益",
            "法人税等",
            "当期純利益"
        ],
        measure=[
            "relative",
            "relative",
            "total",
            "relative",
            "total",
            "relative",
            "relative",
            "total",
            "relative",
            "relative",
            "total",
            "relative",
            "total"
        ],
        y=[1000, -350, 0, -170, 0, 120, -80, 0, 30, -80, 0, -100, 0]
    )
).show()

import plotly
import pandas as pd

stocks = plotly.data.stocks(indexed=True)
stocks.index = pd.to_datetime(stocks.index)
stocks.head()

import plotly.graph_objects as go

ohlc_df = (
    stocks["AMZN"]
    .resample("1M")   # 1週間ごとにリサンプル
    .ohlc()           # 4本値にリサンプル
)
go.Figure(
    [
        go.Candlestick(
            x=ohlc_df.index,
            open=ohlc_df["open"],   # 始値
            high=ohlc_df["high"],   # 高値
            low=ohlc_df["low"],     # 安値
            close=ohlc_df["close"]  # 終値
        )
    ]
).show()

import plotly

election = plotly.data.election()
election.head()

import plotly.graph_objects as go

scatterternary_trace = go.Scatterternary(
    a=election["Bergeron"],     # a軸のデータを設定
    b=election["Coderre"],      # b軸のデータを設定
    c=election["Joly"],         # c軸のデータを設定
    mode="markers",             # 描画モードを設定
    marker={"size": election["total"] * 1e-3}
)
scatterternary_layout = go.Layout(
    ternary={
        "aaxis": {"title": "Bergeron"},     # a軸の名称を設定
        "baxis": {"title": "Coderre"},      # b軸の名称を設定
        "caxis": {"title": "Joly"}          # c軸の名称を設定
    }
)
go.Figure(scatterternary_trace, layout=scatterternary_layout)

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots

np.random.seed(2)
r1 = np.random.rand(6)    # 乱数生成
theta = np.linspace(0, 360, 7)[:-1]
r1_close = np.hstack([r1, np.array(r1[0])])
r2 = r1 + np.random.uniform(-0.3, 0.3, 6)
r2_close = np.hstack([r2, np.array(r2[0])])
label = list("ABCDEF")

polar_fig = make_subplots(
    rows=2,
    cols=2,
    specs=[
        [{"type": "polar"}, {"type": "polar"}],
        [{"type": "polar"}, {"type": "polar"}]
    ]
)
# 点で描画
polar_fig.add_trace(
    go.Scatterpolar(r=r1, theta=theta, mode="markers"), row=1, col=1
)
# 線で描画(レーダチャート)
polar_fig.add_trace(
    go.Scatterpolar(
        r=r1_close, theta=label, mode="lines", fill="toself", name="r1"
    ),
    row=1,
    col=2
)
polar_fig.add_trace(
    go.Scatterpolar(
        r=r2_close, theta=label, mode="lines", fill="toself", name="r2"
    ),
    row=1,
    col=2
)
# 鶏頭図
polar_fig.add_trace(go.Barpolar(r=r1, theta=label), row=2, col=1)
polar_fig.add_trace(go.Barpolar(r=r2, theta=label), row=2, col=1)
polar_fig.show()

import numpy as np
import plotly.graph_objects as go

np.random.seed(3)
z = np.random.randn(5, 5)

go.Figure([go.Contour(z=z)]).show()

import numpy as np
import plotly.graph_objects as go

np.random.seed(9)
x = np.arange(0, 5)
y = np.arange(0, 50, 10)
z = np.random.randn(5, 5)

go.Figure([go.Heatmap(x=x, y=y, z=z)]).show()

import plotly
import plotly.graph_objects as go

tips = plotly.data.tips()

go.Figure(
    [
        go.Parcats(
            dimensions=[
                {"label": "sex", "values": tips["sex"]},
                {"label": "smoker", "values": tips["smoker"]},
                {"label": "day", "values": tips["day"]},
                {"label": "time", "values": tips["time"]}
            ],
            line={"color": tips["size"]}      # size列で色分け
        )
    ]
).show()

import plotly
import plotly.graph_objects as go

iris = plotly.data.iris()

go.Figure(
    [
        go.Parcoords(
            dimensions=[
                {"label": "sepal_length", "values": iris["sepal_length"]},
                {"label": "sepal_width", "values": iris["sepal_width"]},
                {"label": "petal_length", "values": iris["petal_length"]},
                {"label": "petal_width", "values": iris["petal_width"]}
            ],
            line={"color": iris["species_id"]}      # species_idで色分け
        )
    ]
).show()

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots

np.random.seed(2)
x = np.arange(1, 6)
y = np.random.rand(5)

error_fig = make_subplots(rows=2, cols=2)

# エラーバーを一定の値で指定
error_fig.add_trace(
    go.Scatter(
        x=x,
        y=y,
        # エラーバーを定数で指定
        error_y={"type": "constant", "value": 0.1},
    ),
    row=1,
    col=1
)
# 各要素ごとにエラーバーを指定
err_value = np.random.rand(5) * 0.1
error_fig.add_trace(
    go.Scatter(
        x=x,
        y=y,
        # 各要素のエラーバーを指定
        error_x={"type": "data", "array": err_value},
    ),
    row=1,
    col=2
)
# エラーバーを正の値と負の値をそれぞれ指定
err_value_minus = np.random.rand(5) * 0.1
error_fig.add_trace(
    go.Bar(
        x=x,
        y=y,
        error_y={
            "symmetric": False,  			# エラーバーを非対称
            "type": "data",
            "array": err_value,
            "arrayminus": err_value_minus,  # 各要素の負の値を指定
        },
    ),
    row=2,
    col=1
)
error_fig.show()