Plot Data from Salesforce in Python/v3

import plotly
plotly.__version__

import plotly.plotly as py
import plotly.graph_objs as go

import pandas as pd
import numpy as np
from collections import Counter
import requests

from simple_salesforce import Salesforce
requests.packages.urllib3.disable_warnings() # this squashes insecure SSL warnings - DO NOT DO THIS ON PRODUCTION!

with open('salesforce_login.txt') as f:
    username, password, token = [x.strip("\n") for x in f.readlines()]
sf = Salesforce(username=username, password=password, security_token=token)

leads_for_status = sf.query("SELECT Id, Status, Owner.Name FROM Lead")

statuses = [x['Status'] for x in leads_for_status["records"]]
status_counts = Counter(statuses)

data = [go.Bar(x=status_counts.keys(), y=status_counts.values())]
py.iplot(data, filename='salesforce/lead-distributions')

owners = [x['Owner']['Name'] for x in leads_for_status["records"]]

df = pd.DataFrame({'Owners':owners, 'Status':statuses})

lead_comparison = []
for name, vals in df.groupby('Owners'):
    counts = vals.Status.value_counts()
    lead_comparison.append(Bar(x=counts.index, y=counts.values, name=name))

py.iplot(lead_comparison, filename='salesforce/lead-owner-status-groupings')

opportunity_amounts = sf.query("SELECT Id, Probability, StageName, Amount, Owner.Name FROM Opportunity WHERE AMOUNT < 10000")

amounts = [x['Amount'] for x in opportunity_amounts['records']]
owners = [x['Owner']['Name'] for x in opportunity_amounts['records']]

hist1 = go.Histogram(x=amounts)

py.iplot([hist1], filename='salesforce/opportunity-probability-histogram')

df2 = pd.DataFrame({'Amounts':amounts,'Owners':owners})

opportunity_comparisons = []
for name, vals in df2.groupby('Owners'):
    temp = Histogram(x=vals['Amounts'], opacity=0.75, name=name)
    opportunity_comparisons.append(temp)

layout = go.Layout(
    barmode='stack'
)
fig = go.Figure(data=opportunity_comparisons, layout=layout)

py.iplot(fig, filename='salesforce/opportunities-histogram')

from IPython.display import HTML
HTML("""<div>
    <a href="https://plotly.com/~bill_chambers/21/" target="_blank" title="Chuck vs Bill Sales Amounts" style="display: block; text-align: center;"><img src="https://plotly.com/~bill_chambers/21.png" alt="Chuck vs Bill Sales Amounts" style="max-width: 100%;width: 1368px;"  width="1368" onerror="this.onerror=null;this.src='https://plotly.com/404.png';" /></a>
    <script data-plotly="bill_chambers:21" src="https://plotly.com/embed.js" async></script>
</div>""")

large_opps = sf.query("SELECT Id, Name, Probability, ExpectedRevenue, StageName, Amount, CloseDate, Owner.Name FROM Opportunity WHERE StageName NOT IN ('Closed Lost', 'Closed Won') AND Amount > 5000")

large_opps_df = pd.DataFrame(large_opps['records'])
large_opps_df['Owner'] = large_opps_df.Owner.apply(lambda x: x['Name']) # just extract owner name
large_opps_df.drop('attributes', inplace=True, axis=1) # get rid of extra return data from Salesforce
large_opps_df.head()

scatters = []
for name, temp_df in large_opps_df.groupby('Owner'):
    hover_text = temp_df.Name + "<br>Close Probability: " + temp_df.Probability.map(str) + "<br>Stage:" + temp_df.StageName
    scatters.append(
        go.Scatter(
            x=temp_df.CloseDate,
            y=temp_df.Amount,
            mode='markers',
            name=name,
            text=hover_text,
            marker=dict(
                size=(temp_df.Probability / 2) # helps keep the bubbles of managable size
            )
        )
    )

data = scatters
layout = go.Layout(
    title='Open Large Deals',
    xaxis=dict(
        title='Close Date'
    ),
    yaxis=dict(
        title='Deal Amount',
        showgrid=False
    )
)
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='salesforce/open-large-deals-scatter')