def Dist_harga_hasil(lokasi):
df = data_clean()
fig = px.histogram(df[df['neighbourhood_cleansed'] == lokasi],
x="price",
title='Histogram of price in ' + lokasi)
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def Dist_harga():
df = data_clean()
fig = px.box(df,
x="neighbourhood_cleansed",
y="price",
title="Box Plot Price from Neighbourhood")
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def Dist_harga3():
df = data_clean()
series_neigh_price = df.groupby(
'neighbourhood_cleansed').mean()['price'].sort_values()
fig = go.Figure([go.Bar(x=series_neigh_price.index, y=series_neigh_price)],
layout=go.Layout(title='Mean Price from Location'))
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def Dist_harga2():
df = data_clean()
fig = go.Figure(
data=[
go.Pie(labels=df['neighbourhood_cleansed'].value_counts().index,
values=df['neighbourhood_cleansed'].value_counts(),
hole=.3)
],
layout=go.Layout(
title='persentasi neighbourhood cleansed',
margin=go.Margin(
l=0, r=200, b=100, t=100,
pad=4) # Margins - Left, Right, Top Bottom, Padding
))
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def quadrant_plots():
df = data_clean()
df_group = df.QUADRANT.value_counts()
fig = go.Figure([go.Bar(x=df_group.index, y=df_group.values)])
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def ward_plots():
df = data_clean()
df_group2 = df.WARD.value_counts()
fig = go.Figure([go.Bar(x=df_group2.index, y=df_group2.values)])
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json
def Dist_harga1():
df = data_clean()
fig = px.histogram(df, x="price", title="Prices Distribution")
fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return fig_json