I have a csv that I'm attemping to create a histogram of in plotly. The csv contains a date field (in hour increments), a user count field, and an average connection time field. I am attempting to graph the user count field values across time with the following snippet of code. As seen in the code, I am also attempting to re-distribute the xbins based on a user selecting timeframe from a dropdown menu.
Unfortunately it seems like the graph that is generated is not correct because it returns values of 1 or 4 for each day. This does not align with the csv itself which has a variety of users #s per hour.
I'm assuming the issue is the way in which I'm modifying the bins/aggregations but I can't seem to figure out what exactly is wrong. Any help is appreciated.
Histogram:
Code Snippet:
df['END TIME'] = pd.to_datetime(df['END TIME'])
df['END TIME'] = df['END TIME'].dt.round('H')
df.to_csv(r"C:\temp\test.csv")
data = [dict(
x=df['END TIME'],
y=df['USER COUNT'],
autobinx=False,
autobiny=True,
marker=dict(color='rgb(68, 68, 68)'),
name='date',
type='histogram',
xbins=dict(
end= df['END TIME'].max(),
size='3600000',
start=df['END TIME'].min()
)
)]
layout = dict(
paper_bgcolor='rgb(240, 240, 240)',
plot_bgcolor='rgb(240, 240, 240)',
title='<b>User Count</b>',
xaxis=dict(
title='',
type='date'
),
yaxis=dict(
title='User Count',
type='linear'
),
updatemenus=[dict(
x=0.1,
y=1.15,
xref='paper',
yref='paper',
yanchor='top',
active=1,
showactive=True,
buttons=[
dict(
args=['xbins.size', '3600000'],
label='Hour',
method='restyle',
), dict(
args=['xbins.size', 'D1'],
label='Day',
method='restyle',
), dict(
args=['xbins.size', 'M1'],
label='Month',
method='restyle',
), dict(
args=['xbins.size', 'M3'],
label='Quarter',
method='restyle',
), dict(
args=['xbins.size', 'M6'],
label='Half Year',
method='restyle',
), dict(
args=['xbins.size', 'M12'],
label='Year',
method='restyle',
)]
)]
)
fig_dict = dict(data=data, layout=layout)
pio.show(fig_dict, validate=False)
