class DataPlotter:
"""
Formats data to be plotted by Plotly.
"""
def __init__(self):
self.client = CartodbClient()
def get_graph(self, area=None, company=None):
"""
Queries tweets by given area/company filter.
"""
# Get all tweets or filtered by area
if area:
data = self.client.get_tweets_by_area(area)
suffix = area.upper()
elif company:
data = self.client.get_tweets_by_company(company)
suffix = company.upper()
else:
data = self.client.get_all_tweets()
suffix = 'GLOBAL'
processor = DataProcessor(data)
# Get the time series data
time_series = processor.prepare_time_series()
# Save all the graph info in a list we can access from the view template
graph = [
dict(
data=[
dict(
x=time_series.index,
y=time_series
)
],
layout=dict(
title='Tweet Frequency - ' + suffix
),
id = 'timeseries'
)
]
# Plotly needs the graph/pandas data encoded in compatible JSON format
graph = json.dumps(graph, cls=plotly.utils.PlotlyJSONEncoder)
return graph
class DataPlotter:
"""
Formats data to be plotted by Plotly.
"""
def __init__(self):
self.client = CartodbClient()
def get_graph(self, area=None, company=None):
"""
Queries tweets by given area/company filter.
"""
# Get all tweets or filtered by area
if area:
data = self.client.get_tweets_by_area(area)
suffix = area.upper()
elif company:
data = self.client.get_tweets_by_company(company)
suffix = company.upper()
else:
data = self.client.get_all_tweets()
suffix = 'GLOBAL'
processor = DataProcessor(data)
# Get the time series data
time_series = processor.prepare_time_series()
# Save all the graph info in a list we can access from the view template
graph = [
dict(data=[dict(x=time_series.index, y=time_series)],
layout=dict(title='Tweet Frequency - ' + suffix),
id='timeseries')
]
# Plotly needs the graph/pandas data encoded in compatible JSON format
graph = json.dumps(graph, cls=plotly.utils.PlotlyJSONEncoder)
return graph
def __init__(self):
self.client = CartodbClient()
def __init__(self):
self.client = CartodbClient()
