使用两个下拉按钮构建一个 plotly 散点图,一个用于 x 轴,一个用于 y 轴
Build a plotly scatterplot with two drop down buttons one for x and one for y axis
我想构建一个散点图,但使用 2 个下拉菜单,我可以在变量之间切换,一个用于 x 轴,另一个用于 y 轴(例如总测试和总案例,或最近案例和总案例),我尝试通过替换
来构建我找到的解决方案
cols_dd = ["Total tests", "Total cases", "Total deaths"]
for value in cols_dd:
with
cols_dd = {"Total tests":"Total cases", "Total deaths":"Recent cases", "Population":"Total vaccinations"}
k,v in cols_dd.items():
and the using k and v in place of values but it returns an error ('dict_keys' object is not subscriptable)
有人可以分享实现此目的的方法吗,这是我的代码。
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
# get OWID data
df = pd.read_csv(
"https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/latest/owid-covid-latest.csv"
)
# rename columns as sample code uses other names....
df = df.rename(
columns={
"location": "Location",
"iso_code": "Iso code",
"total_tests": "Total tests",
"people_vaccinated_per_hundred": "Vaccines",
"new_cases": "Recent cases",
"total_cases": "Total cases",
"total_deaths": "Total deaths",
"total_vaccinations": "Total vaccinations",
"people_vaccinated": "People vaccinated",
"population": "Population",
"total_boosters": "Vaccination policy",
}
).fillna(0)
cols_dd = {"Total tests":"Total cases", "Total deaths":"Recent cases", "Population":"Total vaccinations"}
fig = go.Figure()
for k,v in cols_dd.items():
fig.add_traces(px.scatter(df, x=k, y=v, color="Location",
hover_data={
"Iso code": False,
"Vaccines": True,
"Total tests": ": ,0.f",
"Recent cases": ": ,0.f",
"Total cases": ": ,0.f",
"Total deaths": ": ,0.f",
"Total vaccinations": ": ,0.f",
"People vaccinated": ": ,0.f",
"Population": ": ,0.f",
"Vaccination policy": ": 0.f",
},
color_continuous_scale="spectral_r",
hover_name="Location",
)
.update_traces(visible=(k == list(cols_dd.keys()[0]))
.data
))
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": value,
"method": "update",
"args": [
{"visible": [v2 == value for v2 in cols_dd]},
{"title": f"<b>{k}</b> vs <b>{v}</b>"},
],
}
for k in cols_dd
]
}
]
)
您可以将所有变量组合构建为轨迹和菜单。
cols_dd = ["Total tests", "Total cases", "Total deaths"]
hd = {
"Iso code": False,
"Vaccines": True,
"Total tests": ": ,0.f",
"Recent cases": ": ,0.f",
"Total cases": ": ,0.f",
"Total deaths": ": ,0.f",
"Total vaccinations": ": ,0.f",
"People vaccinated": ": ,0.f",
"Population": ": ,0.f",
"Vaccination policy": ": 0.f",
}
# px.scatter(df, x="Total cases", y="Total deaths", hover_data=hd, hover_name="Location")
fig = go.Figure()
for k, v in itertools.combinations(cols_dd, 2):
figt = px.scatter(df, x=k, y=v, hover_data=hd, hover_name="Location").update_traces(
visible=False
)
fig = fig.add_traces(figt.data)
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": f"{k} - {v}",
"method": "update",
"args": [
{
"visible": [
(k2 == k and v2 == v)
for k2, v2 in itertools.combinations(cols_dd, 2)
]
},
{"title": f"<b>{k} - {v}</b>"},
],
}
for k, v in itertools.combinations(cols_dd, 2)
]
}
],
margin={"l": 0, "r": 0, "t": 25, "b": 0},
).update_traces(visible=True, selector=0)
独立
cols_dd = ["Total tests", "Total cases", "Total deaths"]
fig = go.Figure(
go.Scatter(
x=df[np.random.choice(cols_dd, 1)[0]],
y=df[np.random.choice(cols_dd, 1)[0]],
hovertemplate='x: %{x} <br>y: %{y}',
mode="markers"
)
)
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": f"x - {x}",
"method": "update",
"args": [
{"x": [df[x]]},
{"xaxis": {"title": x}},
],
}
for x in cols_dd
]
},
{
"buttons": [
{
"label": f"y - {x}",
"method": "update",
"args": [{"y": [df[x]]}, {"yaxis": {"title": x}}],
}
for x in cols_dd
],
"y": 0.9,
},
],
margin={"l": 0, "r": 0, "t": 25, "b": 0},
)
fig
我想构建一个散点图,但使用 2 个下拉菜单,我可以在变量之间切换,一个用于 x 轴,另一个用于 y 轴(例如总测试和总案例,或最近案例和总案例),我尝试通过替换
来构建我找到的解决方案cols_dd = ["Total tests", "Total cases", "Total deaths"]
for value in cols_dd:
with
cols_dd = {"Total tests":"Total cases", "Total deaths":"Recent cases", "Population":"Total vaccinations"}
k,v in cols_dd.items():
and the using k and v in place of values but it returns an error ('dict_keys' object is not subscriptable)
有人可以分享实现此目的的方法吗,这是我的代码。
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
# get OWID data
df = pd.read_csv(
"https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/latest/owid-covid-latest.csv"
)
# rename columns as sample code uses other names....
df = df.rename(
columns={
"location": "Location",
"iso_code": "Iso code",
"total_tests": "Total tests",
"people_vaccinated_per_hundred": "Vaccines",
"new_cases": "Recent cases",
"total_cases": "Total cases",
"total_deaths": "Total deaths",
"total_vaccinations": "Total vaccinations",
"people_vaccinated": "People vaccinated",
"population": "Population",
"total_boosters": "Vaccination policy",
}
).fillna(0)
cols_dd = {"Total tests":"Total cases", "Total deaths":"Recent cases", "Population":"Total vaccinations"}
fig = go.Figure()
for k,v in cols_dd.items():
fig.add_traces(px.scatter(df, x=k, y=v, color="Location",
hover_data={
"Iso code": False,
"Vaccines": True,
"Total tests": ": ,0.f",
"Recent cases": ": ,0.f",
"Total cases": ": ,0.f",
"Total deaths": ": ,0.f",
"Total vaccinations": ": ,0.f",
"People vaccinated": ": ,0.f",
"Population": ": ,0.f",
"Vaccination policy": ": 0.f",
},
color_continuous_scale="spectral_r",
hover_name="Location",
)
.update_traces(visible=(k == list(cols_dd.keys()[0]))
.data
))
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": value,
"method": "update",
"args": [
{"visible": [v2 == value for v2 in cols_dd]},
{"title": f"<b>{k}</b> vs <b>{v}</b>"},
],
}
for k in cols_dd
]
}
]
)
您可以将所有变量组合构建为轨迹和菜单。
cols_dd = ["Total tests", "Total cases", "Total deaths"]
hd = {
"Iso code": False,
"Vaccines": True,
"Total tests": ": ,0.f",
"Recent cases": ": ,0.f",
"Total cases": ": ,0.f",
"Total deaths": ": ,0.f",
"Total vaccinations": ": ,0.f",
"People vaccinated": ": ,0.f",
"Population": ": ,0.f",
"Vaccination policy": ": 0.f",
}
# px.scatter(df, x="Total cases", y="Total deaths", hover_data=hd, hover_name="Location")
fig = go.Figure()
for k, v in itertools.combinations(cols_dd, 2):
figt = px.scatter(df, x=k, y=v, hover_data=hd, hover_name="Location").update_traces(
visible=False
)
fig = fig.add_traces(figt.data)
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": f"{k} - {v}",
"method": "update",
"args": [
{
"visible": [
(k2 == k and v2 == v)
for k2, v2 in itertools.combinations(cols_dd, 2)
]
},
{"title": f"<b>{k} - {v}</b>"},
],
}
for k, v in itertools.combinations(cols_dd, 2)
]
}
],
margin={"l": 0, "r": 0, "t": 25, "b": 0},
).update_traces(visible=True, selector=0)
独立
cols_dd = ["Total tests", "Total cases", "Total deaths"]
fig = go.Figure(
go.Scatter(
x=df[np.random.choice(cols_dd, 1)[0]],
y=df[np.random.choice(cols_dd, 1)[0]],
hovertemplate='x: %{x} <br>y: %{y}',
mode="markers"
)
)
fig.update_layout(
updatemenus=[
{
"buttons": [
{
"label": f"x - {x}",
"method": "update",
"args": [
{"x": [df[x]]},
{"xaxis": {"title": x}},
],
}
for x in cols_dd
]
},
{
"buttons": [
{
"label": f"y - {x}",
"method": "update",
"args": [{"y": [df[x]]}, {"yaxis": {"title": x}}],
}
for x in cols_dd
],
"y": 0.9,
},
],
margin={"l": 0, "r": 0, "t": 25, "b": 0},
)
fig