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View tut01-lesson2-create_party_table.py
def create_party_table(self):
# Panda Data Frame - Table of Tweeter Users per Party
# https://stackoverflow.com/questions/48909110/python-pandas-mean-and-sum-groupby-on-different-columns-at-the-same-time
panda_data = { "Party": self.__col_party,
"PartyCount": self.__col_party, # Duplicate Party column for the counting
"FollowersCount": self.__col_followers_count,
"FriendsCount": self.__col_friends_count
}
df = DataFrame(panda_data , index=self.__labels)
# We use the as_index parameter, so that Party will also be a column of the data frame
View tut01-lesson2-config-CH.yaml
twitterListAccount: "SoMePolis"
twitterListName: "BundesparlamentarierInnen"
# https://www.parlament.ch/de/organe/fraktionen/im-parlament-vertretene-parteien
parties:
- twitter: "spschweiz"
abbrs: ["SP","PS"]
keywords: ["socialist", "sozialist"]
- twitter: "FDP_Liberalen"
abbrs: ["FDP","PLR"]
keywords: ["fdp","plr"]
View tut01-lesson2-checkForParty.py
def __check_for_party(self, user_list):
party_column = []
# iterate through each user account
for user in user_list:
# iterate trough all parties
for party in self.__cfg.get('parties'):
res = "unknown"
# Check first all abbreviations
# We don't do lower here because that could result to false positive
for abbr in party['abbrs']:
View tut01-lesson2-createPoliticanTable.py
def create_politican_table(self):
# Panda Data Frame - Table of all Parliament Members
panda_data = { 'ScreenName' : self.__col_screen_name,
'Name': self.__col_name,
'Description': self.__col_description,
"FollowersCount": self.__col_followers_count,
"FriendsCount": self.__col_friends_count,
"Party": self.__col_party
}
df = DataFrame(panda_data , index=self.__labels)
View tut01-lesson2-main.py
def main():
analyzer_ch = GovernmentSocialMediaAnalyzer("CH")
analyzer_ch.create_politican_table()
analyzer_ch.create_party_table()
View tut01-lesson1-init.py
def __init__(self):
res = {}
# Reading the secret values from a local disk
with open("../../../secret/twitter.yaml", 'r') as stream:
try:
res= yaml.load(stream)
except yaml.YAMLError as exc:
print(exc)
exit(1)
View tut101-lesson1-get_government_members.py
def get_government_members(self):
lists = self.__api.lists_all('SoMePolis')
for list in lists:
if list.name == 'BundesparlamentarierInnen':
result = []
for item in tweepy.Cursor(self.__api.list_members, list_id=list.id).items():
result.append(item)
return result
return None
View tut01-lesson1-create_plotly_table.py
def create_plotly_table(self):
lists = self.get_government_members()
labels = range(0,len(lists))
col1 = [list.screen_name for list in lists]
col2 = [list.name for list in lists]
col3 = [list.description for list in lists]
col4 = [list.followers_count for list in lists]
col5 = [list.friends_count for list in lists]
# Panda Data Set
View tut01-lesson1-auth.py
# attempt authentication
try:
# create OAuthHandler object
auth = OAuthHandler(consumer_key, consumer_secret)
# set access token and secret
auth.set_access_token(access_token, access_token_secret)
# create tweepy API object to fetch tweets
self.__api = tweepy.API(auth)
except:
print("Error: Authentication Failed")
View tut01-charts-lesson3.py
def create_party_friends_count_bar_chart(self, df):
data = [
go.Bar(
x=df.Party, # assign x as the dataframe column 'x'
y=df.FriendsCount
)
]
py.plot(data, filename=self.__country_code+'-tw-party_politicans_count')
def create_party_politicans_count_pie_chart(self, df):