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Youtube 이수안컴퓨터연구소의
Plotly 한번에 끝내기 - 모던한 인터렉티브 시각화 라이브러리 동영상을 보고 요약한 코드입니다!

import plotly.io as pio
import plotly.express as px
import plotly.graph_objects as go
import plotly.figure_factory as ff
from plotly.subplots import make_subplots
from plotly.validators.scatter.marker import SymbolValidator

# 병렬 다이어그램 (Parallel Diagram)

# px.parallel_categories
fig = px.parallel_categories(
    data,
    dimensions = [], # 보고 싶은 데이터만 입력,
    color = ,
    color_continuous_scale = , # px.colors.sequential.Viridis
)
fig.show()

# px.parallel_coordinates
fig = px.parallel_coordinates(
    data,
    color = ,
    dimensions = [],
    color_continuous_scale = , # px.colors.diverging.Armyrose
    color_continous_midpoint = , # 2
)
fig.show()

# 덴드로그램 (Dendrogram)

# ff.create_dendrogram
fig = ff.create_dendrogram(
    x = ,
    color_threshold = , # 덴드로그램 색깔 바뀌는 기준, 1.2
)
fig.update_layout(
    width = ,
    height =
)
fig.show()

# 맵 (maps)

# px.scatter_mapbox
fig = px.scatter_mapbox(
    data,
    lat = ,
    lon = ,
    color = ,
    size = , size_max = ,
    color_continous_scale = , # px.colors.cyclical.Edge,
    mapbox_style = , # 스타일, carto-positron
)
fig.show()

# px.line_mapbox
fig = px.line_mapbox(
    data,
    lat = ,
    lon = ,
    color = ,
    zoom = ,
    height = ,
    width =
)
fig.update_layout(
    mapbox_style = , # stamen-terrain
    mapbox_zoom = ,
    mapbox_center_lat = ,
    margin = {'r':, 't':, 'l':, 'b':}
)
fig.show()

# px.density_mapbox
fig = px.density_mapbox(
    earthquake,
    lat = ,
    lon = ,
    z = ,
    radius = , # 10
    center = dict(
        lat = ,
        lon =
    ),
    zoom = ,
    mapbox_style = # stamen-terrain
)
fig.show()

# px.choropleth_mapbox
fig = px.choropleth_mapbox(
    data,
    geojson = , # json 파일 다운로드
    location = ,
    color = ,
    color_continous_scale = , # blues
    range_color = , # color range 설정 (0, 12)
    mapbox_style = , # carto-positron
    zoom = ,
    center = {'lat' : , 'lon' : },
    opacity = ,
    labels = {'' : ''},
)
fig.update_layout(
    margin = {'r' : , 't' : , 'l' : , 'b' : } # 마진 설정
)
fig.show()

# px.choropleth
fig = px.choropleth(
    data,
    locations = ,
    color = ,
    hover_name = ,
    color_continous_scale = , # px.colors.sequential.Viridis
    animation_frame = , # animation 추가
)
fig.show()

# go.Choropleth
fig = go.Figure(data=go.Choropleth(
    locations = ,
    z = ,
    text = ,
    colorscale = , # solar_r
    autocolorscale = , # False
    reversescale = , # True
    marker_line_color = , # darkgray
    marker_line_width = , # .5
    colorbar_tickprefix = , # %
    colorbar_title =
))
fig.update_layout(
    title_text = ,
    geo = dict(
        showframe = , # False
        showcoastlines = , # False
        projection_type = # equirectangular
    )
)
fig.show()

# 지구본

# go.Scattergeo
fig = go.Figure(go.Scattergeo())
fig.update_geos(
    projection_type = , # orthographic/natural earth
)
fig.update_layout(
    height = ,
    margin = {'r':, 't':, 'l':, 'b'}
)
fig.show()

# px.line_geo
fig = px.line_geo(
    data,
    locations = ,
    color = ,
    projection = , # orthographic
)
fig.show()

# px.scatter_geo
fig = px.scatter_geo(
    data,
    locations = ,
    color = ,
    hover_name = ,
    size = ,
    projection = , # natural_earth
    animation_frame = , # animation 추가
)
fig.show()

# 3D 차트

# px.line_3d
fig = px.line_3d(
    data,
    x = ,
    y = ,
    z = ,
    color =
)
fig.show()

# px.scatter_3d
fig = px.scatter_3d(
    data,
    x = ,
    y = ,
    z = ,
    color = ,
    symbol = ,
    size = ,
    opacity = ,
    hover_data = []
)
fig.update_layout(
    scene_zaxis_type = 'log' # bubble 차트 만들 수 있음
)
fig.show()