I'm developing a visualization chart:
But as you can see: 1 - It has a gap at the start and end of the chart 2 - The tick labels are overlapping
I tried a lot to fix it but I can't find references and I don't know more about what I should try... Does someone know how to fix this properly?
Below is a reproducible code, any help will be really appreciated:
import pandas as pd
import plotly.express as px
data_dict = [{'variable': 'opt1', 'time_seconds': 62.42, 'values': 1.2506616294386024},
{'variable': 'opt1', 'time_seconds': 368.64, 'values': 1.026396270065788},
{'variable': 'opt1', 'time_seconds': 672.04, 'values': 0.9193268790432114},
{'variable': 'opt1', 'time_seconds': 967.76, 'values': 1.0040146519632747},
{'variable': 'opt1', 'time_seconds': 1319.24, 'values': 0.9758039569410012},
{'variable': 'opt1', 'time_seconds': 1621.84, 'values': 0.9608018775714326},
{'variable': 'opt2', 'time_seconds': 62.42, 'values': 53.669690262026634},
{'variable': 'opt2', 'time_seconds': 368.64, 'values': 67.29353920559024},
{'variable': 'opt2', 'time_seconds': 672.04, 'values': 82.30782533848364},
{'variable': 'opt2', 'time_seconds': 1017.26, 'values': 64.92250125677477},
{'variable': 'opt2', 'time_seconds': 1319.24, 'values': 61.70492445574225},
{'variable': 'opt2', 'time_seconds': 1621.84, 'values': 66.73124984237081},
{'variable': 'opt3', 'time_seconds': 62.34, 'values': 67.07091129789107},
{'variable': 'opt3', 'time_seconds': 364.74, 'values': 60.39192699523444},
{'variable': 'opt3', 'time_seconds': 666.68, 'values': 57.13104540996532},
{'variable': 'opt3', 'time_seconds': 967.76, 'values': 50.293945860615096},
{'variable': 'opt3', 'time_seconds': 1317.33, 'values': 73.49109300734065},
{'variable': 'opt3', 'time_seconds': 1619.03, 'values': 80.53859104682748}]
table = pd.DataFrame.from_dict(data_dict)
px.scatter(
table,
x=pd.to_datetime(table['time_seconds'],unit='s'),
y="values",
color="variable",
hover_data=["time_seconds"],
color_discrete_map={
"opt1": "#008aff",
"opt2": "#8c2eff",
"opt3": "#56cb32",
},
).update_traces(mode="lines+markers").for_each_trace(
lambda t: t.update(yaxis="y2") if t.name == "opt1" else t
).update_layout(
yaxis2={"overlaying": "y", "side": "right", "dtick":1},
xaxis_tickformat="%H:%M:%S",
showlegend=False,
title_text=None,
)
Regards,
Leonardo
Explicitly set the range_x
range_x=[
pd.to_datetime(table["time_seconds"], unit="s").min(),
pd.to_datetime(table["time_seconds"], unit="s").max(),
],
import pandas as pd
import plotly.express as px
data_dict = [
{"variable": "opt1", "time_seconds": 62.42, "values": 1.2506616294386024},
{"variable": "opt1", "time_seconds": 368.64, "values": 1.026396270065788},
{"variable": "opt1", "time_seconds": 672.04, "values": 0.9193268790432114},
{"variable": "opt1", "time_seconds": 967.76, "values": 1.0040146519632747},
{"variable": "opt1", "time_seconds": 1319.24, "values": 0.9758039569410012},
{"variable": "opt1", "time_seconds": 1621.84, "values": 0.9608018775714326},
{"variable": "opt2", "time_seconds": 62.42, "values": 53.669690262026634},
{"variable": "opt2", "time_seconds": 368.64, "values": 67.29353920559024},
{"variable": "opt2", "time_seconds": 672.04, "values": 82.30782533848364},
{"variable": "opt2", "time_seconds": 1017.26, "values": 64.92250125677477},
{"variable": "opt2", "time_seconds": 1319.24, "values": 61.70492445574225},
{"variable": "opt2", "time_seconds": 1621.84, "values": 66.73124984237081},
{"variable": "opt3", "time_seconds": 62.34, "values": 67.07091129789107},
{"variable": "opt3", "time_seconds": 364.74, "values": 60.39192699523444},
{"variable": "opt3", "time_seconds": 666.68, "values": 57.13104540996532},
{"variable": "opt3", "time_seconds": 967.76, "values": 50.293945860615096},
{"variable": "opt3", "time_seconds": 1317.33, "values": 73.49109300734065},
{"variable": "opt3", "time_seconds": 1619.03, "values": 80.53859104682748},
]
table = pd.DataFrame.from_dict(data_dict)
px.scatter(
table,
x=pd.to_datetime(table["time_seconds"], unit="s"),
y="values",
color="variable",
hover_data=["time_seconds"],
range_x=[
pd.to_datetime(table["time_seconds"], unit="s").min(),
pd.to_datetime(table["time_seconds"], unit="s").max(),
],
color_discrete_map={
"opt1": "#008aff",
"opt2": "#8c2eff",
"opt3": "#56cb32",
},
).update_traces(mode="lines+markers").for_each_trace(
lambda t: t.update(yaxis="y2") if t.name == "opt1" else t
).update_layout(
yaxis2={"overlaying": "y", "side": "right", "dtick": 1},
xaxis_tickformat="%H:%M:%S",
showlegend=False,
title_text=None,
)