def firstEnter():
y = []
file = open('Trainee Analyst Test DataSet - FirstEnter.csv', 'r')
x = [str(a) for a in file.read().split()]
for k in range(2, len(x), 1):
y.append([str(a) for a in x[k].split(',')])
stages = [int(0) for num in range(0, 9, 1)]
for z in range(0, len(y), 1):
stages[int(y[z][1])] = stages[int(y[z][1])] + 1
for i in range(0, 8, 1):
for l in range(i + 1, 9, 1):
stages[i] = stages[i] + stages[l]
config = {
'displaylogo': False,
'toImageButtonOptions': {
'format': 'png', # one of png, svg, jpeg, webp
'filename': 'FirstEnter',
'height': 800,
'width': 1200,
'scale':
1 # Multiply title/legend/axis/canvas sizes by this factor
}
}
file.close()
fig = go.Figure(go.Funnel(y=[int(num) for num in range(0, 9, 1)],
x=stages))
fig.show(config=config)
def funnel_chart():
tmp = df["Funnel"].value_counts().reset_index()
df2 = pd.DataFrame({"index": ["All"], "Funnel": [tmp["Funnel"].sum()]})
tmp = tmp.append(df2, ignore_index=True, sort=True)
tmp.sort_values("Funnel", ascending=False, inplace=True)
fig = go.Figure(
go.Funnel(y=tmp['index'],
x=tmp['Funnel'],
textposition="inside",
textinfo="value+percent initial",
opacity=0.65,
marker={
"color": ["deepskyblue", "lightsalmon", "tan", "teal"],
"line": {
"width": [4, 2, 3, 1],
"color": ["wheat", "blue", "wheat", "wheat"]
}
},
connector={
"line": {
"color": "royalblue",
"dash": "dot",
"width": 3
}
}))
fig.update_layout(title="CORE CUSTOMER LOOKALIKE PROFILES",
title_x=.5,
margin=dict(t=50))
return fig
def plot_stacked_funnel(groups):
data = []
for t in groups.keys():
trace = go.Funnel(name=t,
y=groups[t]['targets'],
x=groups[t]['values'],
textinfo="value+percent initial+percent previous")
data.append(trace)
layout = go.Layout(margin={
"l": 180,
"r": 0,
"t": 30,
"b": 0,
"pad": 0
},
funnelmode="stack",
showlegend=True,
hovermode='closest',
legend=dict(orientation="v",
bgcolor='#E2E2E2',
xanchor='left',
font=dict(size=12)))
fig = go.Figure(data, layout)
plot_name = 'funnel_plot_{}'.format(datetime.now()).replace(
':', '_').replace('.', '_') + '.html'
path = _.rete.retention_config['experiments_folder'] + '/' + plot_name
fig.write_html(path)
return fig
from plotly import graph_objects as go
fig = go.Figure()
fig.add_trace(
go.Funnel(name='Montreal',
y=[
"Website visit", "Downloads", "Potential customers",
"Requested price"
],
x=[120, 60, 30, 20],
textinfo="value+percent initial"))
fig.add_trace(
go.Funnel(name='Toronto',
orientation="h",
y=[
"Website visit", "Downloads", "Potential customers",
"Requested price", "invoice sent"
],
x=[100, 60, 40, 30, 20],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name='Vancouver',
orientation="h",
y=[
"Website visit", "Downloads", "Potential customers",
"Requested price", "invoice sent", "Finalized"
],
#Create stacked bar chart to look at the number of website registrations completed by each gender within an ad set
stacked_bar(ads, 'Ad Set Name', 'Gender', 'Website Registrations Completed')
# In[22]:
#Create stakced bar chart to examine website registrations completed by different age groups for each ad set
stacked_bar(ads, 'Ad Set Name', 'Age', 'Website Registrations Completed')
# In[27]:
#Find the values for the funnel inputs
funnel_features = [
"Impressions", "Link Clicks", "Website Leads",
"Website Registrations Completed", 'Ad Set Name'
]
funnel_stats = ads[funnel_features].groupby('Ad Set Name').sum()
funnel_stats.head()
# In[28]:
data = funnel_stats.loc['13', :]
# In[29]:
#Examine conversion cycle funnel for ad set 13
fig = go.Figure(
go.Funnel(x=data.values, y=data.index, textinfo="value+percent initial"))
fig.show()
# Now that I have a general idea for the data, I will extract the data and create the dashboard to include an interactive analysis of the ad set performance.
df_mtl = pd.DataFrame(dict(number=[39, 27.4, 20.6, 11, 3], stage=stages))
df_mtl['office'] = 'Montreal'
df_toronto = pd.DataFrame(dict(number=[52, 36, 18, 14, 5], stage=stages))
df_toronto['office'] = 'Toronto'
df = pd.concat([df_mtl, df_toronto], axis=0)
fig = px.funnel(df, x='number', y='stage', color='office')
fig.show()
# In[ ]:
from plotly import graph_objects as go
fig = go.Figure(go.Funnel(
y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],
x = [39, 27.4, 20.6, 11, 2]))
fig.show()
# In[ ]:
from plotly import graph_objects as go
fig = go.Figure(go.Funnel(
y = ["Website visit", "Downloads", "Potential customers", "Requested price", "Finalized"],
x = [39, 27.4, 20.6, 11, 2],
textposition = "inside",
textinfo = "value+percent initial",
def services_cost_viz():
fig = go.Figure()
fig.add_trace(
go.Funnel(name='Netflix',
y=["Premium", "Standard", "Basic"],
x=[17.99, 13.99, 8.99],
textinfo="value+percent initial"))
fig.add_trace(
go.Funnel(name='Hulu',
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[70.99, 11.99, 5.99],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Youtube Premium",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[64.99, 11.99, 0.00],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Sling TV",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[50.00, 35.00, 0.00],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Disney Plus",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[69.99, 6.99, 0.00],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Peacock TV",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[9.99, 4.99, 0.00],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Amazon Prime Video",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[12.99, 8.99, 6.99],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Crunchyroll",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[14.99, 9.99, 7.99],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name="Funimation",
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[99.99, 7.99, 5.99],
textposition="inside",
textinfo="value+percent previous"))
fig.add_trace(
go.Funnel(name='Apple One',
orientation="h",
y=["Premium", "Standard", "Basic"],
x=[29.95, 19.95, 4.99],
textposition="outside",
textinfo="value+percent total"))
#fig.show()
#fig.write_html("templates/services_cost_viz.html")
return render_template("services_cost_viz.html")
fig.add_trace(go.Sankey(orientation='h',
node=dict(pad=10,
thickness=1,
line=dict(width=0),
label=labels,
groups=[]),
link=dict(source=s['source'].values,
target=s['target'].values,
value=s['value'].values,
color=s['color'])),
row=1,
col=2)
fig.add_trace(go.Funnel(orientation='v',
name='川普我最牛',
y=pos_tweets_count['cumsum'],
x=[str(i) for i in pos_tweets_count.index],
marker=dict(color='DarkOliveGreen'),
textinfo="value+percent initial"),
row=1,
col=1)
fig.add_trace(go.Funnel(orientation='v',
name='还行吧',
y=neu_tweets_count['cumsum'],
x=[str(i) for i in pos_tweets_count.index],
marker=dict(color='MidnightBlue'),
textinfo="value+percent initial"),
row=1,
col=1)
fig.add_trace(go.Funnel(orientation='v',
name='小心我怼你',
df_toronto['office'] = 'Москва'
df = pd.concat([df_mtl, df_toronto], axis=0)
fig = px.funnel(df,
x='number',
y='stage',
color='office',
title='Сравнительная воронка продаж')
fig.show()
# 3) Basic Funnel Chart with graph_objects trace go.Funnel
from plotly import graph_objects as go
fig = go.Figure(
go.Funnel(y=[
"Посещения сайта", "Загрузки", "Потенциальные клиенты",
"Запрос о цене", "Выставлен счёт"
],
x=[39, 27.4, 20.6, 11, 2]))
fig.show()
# 4) Setting Marker Size and Color
fig = go.Figure(
go.Funnel(
y=[
"Посещения сайта", "Загрузки", "Потенциальные клиенты",
"Запрос о цене", "Выставлен счёт"
],
x=[39, 27.4, 20.6, 11, 2],
textposition="inside",
textinfo="value+percent initial",
