def get_new_signup(yesterday):
"""
Get yesterday new signup.
Parameters
----------
yesterday: date
Yesterday's date.
Global Variables
----------
api_creator_secret: Mixpanel Creator Project API key.
Use to make API calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe containing user IDs and emails of creators who signed up yesterday.
"""
# New Signup Web
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "New Signup Web"
}],
'from_date': yesterday,
'to_date': yesterday
}),
people=People({'user_selectors': []}),
join_params={
'type': 'full',
'selectors': [{
'event': "New Signup Web"
}]
})
#store email, user id, and sign up events
email_list = []
userid_list = []
for row in query.send():
if 'user' in list(row.keys()):
if '$username' in list(row['user']['properties'].keys()):
userid_list.append(row['user']['properties']['$username'])
if '$email' in list(row['user']['properties'].keys()):
email_list.append(row['user']['properties']['$email'])
#create dataframe
data = {'user_id': userid_list, 'email': email_list}
df_new_users = pd.DataFrame(data=data)
return df_new_users
def AppStart_pull(from_date, to_date):
"""
Pull app user AppStart events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_user_secret: str
Client secret used to make calls to Mixpanel User Project.
Returns
----------
dataframe
Dataframe contains user IDs and AppStart event count for app users in Mixpanel.
"""
#generate JQL query
query = JQL(api_user_secret,
events=Events({
'event_selectors': [{
'event': "AppStart"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(keys=["e.properties.zUserId"],
accumulator=Reducer.count())
#initalize lists to record user ID and AppStarts
user_id_list = []
AppStart_list = []
#process query results
for row in query.send():
if row['key'][0] is not None:
user_id_list.append(int(row['key'][0]))
AppStart_list.append(row['value'])
#generate dataframe
data = {'user_id': user_id_list, 'AppStart': AppStart_list}
df_AppStart = pd.DataFrame(data)
df_AppStart = df_AppStart.dropna()
df_AppStart.user_id = df_AppStart.user_id.astype(int)
return df_AppStart
def _try_invalid_join(self, params):
try:
JQL(api_secret="asas",
events=Events(),
people=People(),
join_params=params)
self.fail("Expected Events syntax error with params: %s" % params)
except JQLSyntaxError as e:
return e
def New_Signup_Web_pull(from_date, to_date):
"""
Pull app creator sign up events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_creator_secret: str
Client secret used to make calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe contains user IDs and new sign up event count for app creators in Mixpanel.
"""
#generate JQL query
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "New Signup Web"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(
keys=[
"e.properties.userId", #use userId
],
accumulator=Reducer.count())
#initialize lists to record user IDs and New Signup Web
user_id_list = []
new_sign_up_list = []
for row in query.send():
if row['key'][0] is not None:
user_id_list.append(int(row['key'][0]))
new_sign_up_list.append(row['value'])
#generate dataframe
data = {'user_id': user_id_list, 'new_sign_up': new_sign_up_list}
df_New_Signup_Web = pd.DataFrame(data)
return df_New_Signup_Web
def test_event_date_keys(self):
for k in ('to_date', 'from_date'):
for v in ('2017-10-19', datetime(2017, 10,
19), datetime(2017, 10,
19).date()):
q = Events({k: v})
self.assertIn('2017-10-19', str(q))
# Now a bad key.
e = self._try_invalid_events({'to_date': 232})
self.assertEqual(str(e),
'to_date must be datetime, datetime.date, or str')
def test_join_types(self):
# Good types
for t in ('full', 'left', 'right', 'inner'):
JQL('some_key',
events=Events(),
people=People(),
join_params={'type': t})
# Bad type
e = self._try_invalid_join({'type': 'mew'})
self.assertEqual(
'"mew" is not a valid join type (valid types: full, left, right, inner)',
str(e))
def test_join_selectors(self):
def good_params():
return {
'selectors': [{
'event': 'my_event',
'selector': 'my selector'
}]
}
# Test valid
JQL('some_api_key',
events=Events(),
people=People(),
join_params=good_params())
# Bad array
bad_params = good_params()
bad_params['selectors'] = 3
e = self._try_invalid_join(bad_params)
self.assertEqual(str(e), "join_params['selectors'] must be iterable")
# Bad key types
for key in ('event', 'selector'):
bad_params = good_params()
bad_params['selectors'][0][key] = 3
e = self._try_invalid_join(bad_params)
self.assertEqual(
str(e),
"join_params['selectors'][0].%s must be a string" % key)
# Bad key
bad_params = good_params()
bad_params['selectors'][0]['mrao'] = 3
e = self._try_invalid_join(bad_params)
self.assertEqual(
str(e), "'mrao' is not a valid key in join_params['selectors'][0]")
def test_event_event_selectors(self):
def good_params():
return {
'event_selectors': [{
'event': 'my_event',
'selector': 'my selector',
'label': 'my label'
}]
}
# Test valid
Events(good_params())
# Bad array
bad_params = good_params()
bad_params['event_selectors'] = 3
e = self._try_invalid_events(bad_params)
self.assertEqual(str(e),
"event_params['event_selectors'] must be iterable")
# Bad key types
for key in ('event', 'selector', 'label'):
bad_params = good_params()
bad_params['event_selectors'][0][key] = 3
e = self._try_invalid_events(bad_params)
self.assertEqual(
str(e),
"event_params['event_selectors'][0].%s must be a string" % key)
# Bad key
bad_params = good_params()
bad_params['event_selectors'][0]['mrao'] = 3
e = self._try_invalid_events(bad_params)
self.assertEqual(
str(e),
"'mrao' is not a valid key in event_params['event_selectors'][0]")
def user_appstart_pull(from_date, to_date):
"""
Pull app user AppStart events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_user_secret: str
Client secret used to make calls to Mixpanel User Project.
Returns
----------
df_user_AppStart: dataframe
Dataframe contains app creator user ID and number of app users.
"""
#generate JQL query
query = JQL(api_user_secret,
events=Events({
'event_selectors': [{
'event': "AppStart"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(
keys=["e.properties.zUserId", "e.properties.zAppOwnerId"],
accumulator=Reducer.count())
#initialize lists to record app user IDs, app creator IDs, app name, and number of AppStarts
app_user_id_list = []
owner_id_list = []
AppStart_list = []
#process query results
for row in query.send():
if (row['key'][0] is not None) & (row['key'][1] is not None):
app_user_id_list.append(int(row['key'][0]))
owner_id_list.append(int(row['key'][1]))
AppStart_list.append(row['value'])
#generate email
data = {
'app_user_id': app_user_id_list,
'creator_id': owner_id_list,
'AppStart': AppStart_list
}
df_AppStart = pd.DataFrame(data)
#make sure IDs are valid
df_user_AppStart = df_AppStart[(df_AppStart.app_user_id > 1)
& (df_AppStart.creator_id > 1)]
return df_user_AppStart
def test_query_plan(self):
with warnings.catch_warnings(record=True) as w:
q = JQL('key', events=Events(), people=People())
q.query_plan()
self.assertIs(w[-1].category, DeprecationWarning)
self.assertIn('query_plan', str(w[-1].message))
def EditorAction_pull(from_date, to_date):
"""
Pull app creator EditorAction-Save events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_creator_secret: str
Client secret used to make calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe contains app creator emails, number of EditorAction events, and zEvent = Save filter.
"""
#generate JQL query
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "EditorAction"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(
keys=["e.properties.zUserEmail", "e.properties.zEvent"],
accumulator=Reducer.count())
#initialize lists to record emails, EditorAction events, and zEvent
user_email_list = []
EditorAction_list = []
zevent_list = []
#process query results
for row in query.send():
if row['key'][0] is not None:
user_email_list.append(row['key'][0])
zevent_list.append(row['key'][1])
EditorAction_list.append(row['value'])
#create dataframe
data = {
'email': user_email_list,
'zevent': zevent_list,
'EditorAction': EditorAction_list
}
df_editor_action = pd.DataFrame(data)
#filter to only include "Save" editor events
df_editor_action = df_editor_action[df_editor_action.zevent == 'Save']
return df_editor_action
def user_appstart_pull(from_date, to_date, df_app_users):
"""
Pull app user AppStart events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_user_secret: str
Client secret used to make calls to Mixpanel User Project.
Returns
----------
df_user_AppStart: dataframe
Dataframe contains app creator user ID, list of app user email domains, and number of app users
df_top_appstarts: dataframe
Dataframe contains app creator user ID and number of AppStarts from top apps
"""
#generate JQL query
query = JQL(api_user_secret,
events=Events({
'event_selectors': [{
'event': "AppStart"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(keys=[
"e.properties.zUserId", "e.properties.zAppOwnerId",
"e.properties.zAppName"
],
accumulator=Reducer.count())
#initialize lists to record app user IDs, app creator IDs, app name, and number of AppStarts
app_user_id_list = []
owner_id_list = []
app_name_list = []
AppStart_list = []
#process query results
for row in query.send():
if row['key'][0] is not None:
app_user_id_list.append(row['key'][0])
owner_id_list.append(row['key'][1])
app_name_list.append(row['key'][2])
AppStart_list.append(row['value'])
#generate email
data = {
'app_user_id': app_user_id_list,
'user_id': owner_id_list,
'app_name': app_name_list,
'AppStart': AppStart_list
}
df_AppStart = pd.DataFrame(data)
#merge AppStart and app user dataframes to associate app user emails to number of AppStarts
df_AppStart = pd.merge(df_AppStart,
df_app_users,
on='app_user_id',
how='left')
#get total users and list of user emails for each app creator
df_user_AppStart = df_AppStart.groupby(
['user_id', 'app_user_id'])['app_name'].count().reset_index()
df_user_AppStart = df_user_AppStart.groupby(
'user_id')['app_user_id'].count().reset_index()
df_user_AppStart = df_user_AppStart.rename(
columns={'app_user_id': 'num_app_users'})
#get app user domain list for each app creator
df_AppStart_temp = df_AppStart.groupby(
['user_id', 'app_user_id',
'user_email'])['app_name'].count().reset_index()
df_AppStart_temp['user_email_domains'] = df_AppStart_temp[
'user_email'].str.split('@').str[1].fillna('')
df_AppStart_temp = df_AppStart_temp[
df_AppStart_temp['user_email_domains'] != '']
df_user_domains_by_creators = df_AppStart_temp.groupby(
'user_id')['user_email_domains'].apply(list).reset_index()
df_user_AppStart = pd.merge(df_user_AppStart,
df_user_domains_by_creators,
on='user_id',
how='left')
df_user_AppStart.loc[df_user_AppStart['user_email_domains'].isnull(),
['user_email_domains']] = df_user_AppStart.loc[
df_user_AppStart['user_email_domains'].isnull(),
'user_email_domains'].apply(lambda x: [])
#only keep the app with the highest number of AppStarts for each app creator
df_top_appstarts = df_AppStart.groupby(
['user_id', 'app_name']).AppStart.sum().reset_index().sort_values(
'AppStart', ascending=False).drop_duplicates('user_id',
keep='first')
df_top_appstarts = df_top_appstarts.rename(
columns={'AppStart': 'appstart_by_top_app'})
return df_user_AppStart, df_top_appstarts
def _try_invalid_events(self, params):
try:
Events(params)
self.fail("Expected Events syntax error with params: %s" % params)
except JQLSyntaxError as e:
return e
def Editor_pull(from_date, to_date):
"""
Pull app creator Editor events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_creator_secret: str
Client secret used to make calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe contains user IDs, Editor event datetime, and Editor event count for app creators in Mixpanel.
"""
#generate JQL query
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "Editor"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(keys=[
"e.properties.zUserId", "new Date(e.time).toISOString()"
],
accumulator=Reducer.count())
#store user IDs, Editor count, and Editor datetime
user_id_list = []
datetime_list = []
Editor_list = []
for row in query.send():
if row['key'][0] is not None:
user_id_list.append(int(row['key'][0]))
datetime_list.append(
datetime.strptime(row['key'][1][:10], '%Y-%m-%d'))
Editor_list.append(row['value'])
#generate dataframe
data = {
'user_id': user_id_list,
'Editor_datetime': datetime_list,
'Editor': Editor_list
}
df_Editor = pd.DataFrame(data)
return df_Editor
def user_appstart_pull(from_date, to_date):
"""
Pull app user AppStart events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_user_secret: str
Client secret used to make calls to Mixpanel User Project.
Returns
----------
df_user_AppStart: dataframe
Dataframe contains app creator user ID and number of app users.
"""
#generate JQL query
query = JQL(api_user_secret,
events=Events({
'event_selectors': [{
'event': "AppStart"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(keys=[
"e.properties.zUserId", "e.properties.zAppOwnerId",
"new Date(e.time).toISOString()"
],
accumulator=Reducer.count())
#initialize lists to record app user IDs, app creator IDs, app name, and number of AppStarts
app_user_id_list = []
owner_id_list = []
AppStart_list = []
date_list = []
#process query results
for row in query.send():
if (row['key'][0] is not None) & (row['key'][1] is not None):
app_user_id_list.append(int(row['key'][0]))
owner_id_list.append(int(row['key'][1]))
date_list.append(datetime.strptime(row['key'][2][:10], '%Y-%m-%d'))
AppStart_list.append(row['value'])
#generate email
data = {
'date': date_list,
'app_user_id': app_user_id_list,
'user_id': owner_id_list,
'AppStart': AppStart_list
}
df_AppStart = pd.DataFrame(data)
#make sure IDs are valid
df_AppStart = df_AppStart[(df_AppStart.app_user_id > 1)
& (df_AppStart.user_id > 1)]
#remove duplicate users on the same day. Since it was pulled based on timestamp, AppStarts in one day can be on multiple roads
df_AppStart = df_AppStart.drop_duplicates(
['user_id', 'date', 'app_user_id'])
#get total users and list of user emails for each app creator
df_user_AppStart = df_AppStart.groupby(
['user_id', 'date']).app_user_id.count().reset_index()
df_user_AppStart = df_user_AppStart.rename(
columns={'app_user_id': 'num_app_users'})
return df_user_AppStart
def New_Signup_Web_pull(from_date, to_date):
"""
Pull app creator sign up events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_creator_secret: str
Client secret used to make calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe contains user IDs, sign up datetime, new sign up event count, and country for app creators in Mixpanel.
"""
#generate JQL query
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "New Signup Web"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(keys=[
"e.properties.userId", "new Date(e.time).toISOString()"
],
accumulator=Reducer.count())
#store emails, user IDs, sign up datetime, and country
user_id_list = []
datetime_list = []
new_sign_up_list = []
for row in query.send():
if row['key'][0] is not None:
user_id_list.append(int(row['key'][0]))
datetime_list.append(
datetime.strptime(row['key'][1][:10], '%Y-%m-%d'))
new_sign_up_list.append(row['value'])
#generate dataframe
data = {
'app_owner_id': user_id_list,
'date': datetime_list,
'new_sign_up': new_sign_up_list
}
df_New_Signup_Web = pd.DataFrame(data)
#only keeping ones with actual IDs
df_New_Signup_Web = df_New_Signup_Web[df_New_Signup_Web.app_owner_id > 1]
return df_New_Signup_Web
def setUp(self):
self.query = JQL(api_secret=None, events=Events())
def pull_usage(from_date, to_date):
"""
Pull usage events in Mixpanel.
Parameters
----------
from_date: date
Start date of query.
to_date: date
End date of query.
Global Variables
----------
api_creator_secret: str
Client secret used to make calls to Mixpanel Creator Project.
Returns
----------
dataframe
Dataframe contains app ID, user IDs, owner ID, and usage event count in Mixpanel.
"""
#generate JQL query
query = JQL(api_creator_secret,
events=Events({
'event_selectors': [{
'event': "Usage"
}],
'from_date': from_date,
'to_date': to_date
})).group_by(
keys=["e.properties.OwnerId", "e.properties.UserId"],
accumulator=Reducer.count())
#store app owner, app, and app user IDs
app_owner_id_list = []
app_user_id_list = []
usage_list = []
for row in query.send():
if row['key'][0] is not None:
app_owner_id_list.append(int(row['key'][0]))
app_user_id_list.append(int(row['key'][1]))
usage_list.append(row['value'])
#generate dataframe
data = {
'app_owner_id': app_owner_id_list,
'app_user_id': app_user_id_list,
'usage': usage_list
}
df_usage = pd.DataFrame(data)
#only keep app owners and users with proper IDs
df_usage = df_usage[(df_usage.app_owner_id > 1)
& (df_usage.app_user_id > 1)]
df_usage = df_usage[~df_usage.app_owner_id.isin(
[10305, 71626])] #remove for demo accounts
return df_usage
def New_Signup_App_pull(yesterday):
"""
Pull app user sign up events in Mixpanel.
Parameters
----------
yesterday: date
Yesterday's date.
Global Variables
----------
api_user_secret: str
Client secret used to make calls to Mixpanel User Project.
Returns
----------
dataframe
Dataframe contains user IDs, sign up datetime, and new sign up event count for app users in Mixpanel.
"""
#generate JQL query
query = JQL(api_user_secret,
events=Events({
'event_selectors': [{
'event': "New Signup App"
}],
'from_date': yesterday,
'to_date': yesterday
})).group_by(keys=[
"e.properties.zUserId", "new Date(e.time).toISOString()"
],
accumulator=Reducer.count())
#initialize lists to store emails, user IDs, and sign up datetime
user_id_list = []
datetime_list = []
new_sign_up_list = []
#process query results
for row in query.send():
if row['key'][0] is not None:
user_id_list.append(int(row['key'][0]))
datetime_list.append(
datetime.strptime(row['key'][1][:10], '%Y-%m-%d'))
new_sign_up_list.append(row['value'])
#generate dataframe
data = {
'app_user_id': user_id_list,
'sign_up_datetime': datetime_list,
'new_signup_app': new_sign_up_list
}
df_New_Signup_App = pd.DataFrame(data)
return df_New_Signup_App
