I have gold price dataset , where first column is date on yyyy-mm-dd format and the second column is gold price.
2019-12-03 1477.60
2019-12-04 1474.45
2019-12-05 1448.40
Is there any way to make animation lineplot with python plotly where I can show gold price change along with date?
Yes, I show you an example.
The effect is fancy but you don't gain much because it is a two dimensional data, I could say indeed you are delaying the data display with no reason.
Usually animations are nice for showing 3 dimensions and obviously using the time as extra dimension to perform the animation, like the first example at plotly web animation documentation: https://plotly.com/python/animations/
import plotly.graph_objects as go
import pandas as pd
# Maybe you needed to display plot in jupyter notebook
import plotly.offline as pyo
pyo.init_notebook_mode()
# Load exmples data
dates = ["2019-12-03", "2019-12-04", "2019-12-05", "2019-12-06",
"2019-12-07", "2019-12-08", "2019-12-09"]
value_gold = [1477.60, 1474.45, 1448.40, 1447.40, 1444.40, 1449.40, 1441.40]
value_bitcoin = [1577.60, 1564.45, 1568.40, 1537.40, 1584.40, 1529.40, 1571.40]
df = pd.DataFrame(list(zip(dates, value_gold, value_bitcoin)),
columns=['date', 'value_gold', 'value_bitcoin'])
# Base plot
fig = go.Figure(
layout=go.Layout(
updatemenus=[dict(type="buttons", direction="right", x=0.9, y=1.16), ],
xaxis=dict(range=["2019-12-02", "2019-12-10"],
autorange=False, tickwidth=2,
title_text="Time"),
yaxis=dict(range=[1400, 1600],
autorange=False,
title_text="Price"),
title="Gold - Bitcoin prices evolution",
))
# Add traces
init = 1
fig.add_trace(
go.Scatter(x=df.date[:init],
y=df.value_gold[:init],
name="Gold",
visible=True,
line=dict(color="#33CFA5", dash="dash")))
fig.add_trace(
go.Scatter(x=df.date[:init],
y=df.value_bitcoin[:init],
name="Bitcoin",
visible=True,
line=dict(color="#bf00ff", dash="dash")))
# Animation
fig.update(frames=[
go.Frame(
data=[
go.Scatter(x=df.date[:k], y=df.value_gold[:k]),
go.Scatter(x=df.date[:k], y=df.value_bitcoin[:k])]
)
for k in range(init, len(df)+1)])
# Extra Formatting
fig.update_xaxes(ticks="outside", tickwidth=2, tickcolor='white', ticklen=10)
fig.update_yaxes(ticks="outside", tickwidth=2, tickcolor='white', ticklen=1)
fig.update_layout(yaxis_tickformat=',')
fig.update_layout(legend=dict(x=0, y=1.1), legend_orientation="h")
# Buttons
fig.update_layout(
updatemenus=[
dict(
buttons=list([
dict(label="Play",
method="animate",
args=[None, {"frame": {"duration": 1000}}]),
dict(label="Gold",
method="update",
args=[{"visible": [False, True]},
{"showlegend": True}]),
dict(label="Bitcoin",
method="update",
args=[{"visible": [True, False]},
{"showlegend": True}]),
dict(label="All",
method="update",
args=[{"visible": [True, True, True]},
{"showlegend": True}]),
]))])
fig.show()
