def analysis(request):
if request.method == "GET":
version = random.randint(0, 1000)
search_dict = request.GET.dict()
filter_dict = {}
for key, value in search_dict.items():
# Bench
if key == "movement1" and value == "bench1":
for key, value in search_dict.items():
if value != '' and value != "None" and key != "movement1":
filter_dict[key] = value
if len(filter_dict) > 0:
print(filter_dict)
filtered_movements = BenchMovement.objects.\
filter(user_id=request.user.id).filter(**filter_dict)
max_weight = []
for workout in filtered_movements:
max_weight.append(workout.movement_weight)
line_chart = pygal.Line(style=NeonStyle)
line_chart.title = 'Lift Progression'
line_chart.x_labels = map(str, range(1, len(max_weight)))
line_chart.add('Bench', max_weight)
line_chart.render_to_file(IMAGE_PATH +
'tracker/static/tmp/chart.svg')
# Deadlift
if key == "movement1" and value == "deadlift1":
for key, value in search_dict.items():
if value != '' and value != "None" and key != "movement1":
filter_dict[key] = value
if len(filter_dict) > 0:
print(filter_dict)
filtered_movements = DeadliftMovement.objects.\
filter(user_id=request.user.id).filter(**filter_dict)
max_weight = []
for workout in filtered_movements:
max_weight.append(workout.movement_weight)
line_chart = pygal.Line(style=NeonStyle)
line_chart.title = 'Lift Progression'
line_chart.x_labels = map(str, range(1, len(max_weight)))
line_chart.add('Deadlift', max_weight)
line_chart.render_to_file(IMAGE_PATH +
'tracker/static/tmp/chart.svg')
# Squat
if key == "movement1" and value == "squat1":
for key, value in search_dict.items():
if value != '' and value != "None" and key != "movement1":
filter_dict[key] = value
if len(filter_dict) > 0:
print(filter_dict)
filtered_movements = SquatMovement.objects.\
filter(user_id=request.user.id).filter(**filter_dict)
max_weight = []
for workout in filtered_movements:
max_weight.append(workout.movement_weight)
line_chart = pygal.Line(style=NeonStyle)
line_chart.title = 'Lift Progression'
line_chart.x_labels = map(str, range(1, len(max_weight)))
line_chart.add('Squat', max_weight)
line_chart.render_to_file(IMAGE_PATH +
'tracker/static/tmp/chart.svg')
# Upper
if key == "movement1" and value == "upper1":
for key, value in search_dict.items():
if value != '' and value != "None" and key != "movement1":
filter_dict[key] = value
if len(filter_dict) > 0:
print(filter_dict)
filtered_movements = SquatMovement.objects.\
filter(user_id=request.user.id).filter(**filter_dict)
max_weight = []
for workout in filtered_movements:
max_weight.append(workout.movement_weight)
line_chart = pygal.Line(style=NeonStyle)
line_chart.title = 'Lift Progression'
line_chart.x_labels = map(str, range(1, len(max_weight)))
line_chart.add('Squat', max_weight)
line_chart.render_to_file(IMAGE_PATH +
'tracker/static/tmp/chart.svg')
upperform = UpperForm()
lowerform = LowerForm()
return render(request, 'tracker/analysis.html', {
'upper_form': upperform,
'lower_form': lowerform,
'version': version
})
def render(self, name=''):
values = [
self.generation.current_generation(self.day * self.iterations +
self.time_step - 1),
self._compute_tcl_power() + np.sum([l.load() for l in self.loads]),
np.average([tcl.SoC for tcl in self.tcls]) * 100,
self.temperatures[self.day * self.iterations + self.time_step - 1],
np.average([l.load() for l in self.loads]), self.sale_price,
self.battery.SoC * 100, self.energy_sold, self.energy_bought,
self.grid.buy_prices[self.day * self.iterations + self.time_step -
1],
self.grid.sell_prices[self.day * self.iterations + self.time_step -
1], self.control,
self._compute_tcl_power()
]
for index, key in enumerate(RENDER_VALUES_dict.keys()):
RENDER_VALUES_dict[key].append(values[index])
if self.time_step == self.iterations:
self.html_file = open("app/templates/figure.html", 'w')
self.html_file.write("{% extends \"base.html\" %}" + "\n" +
"{% block content %}" + "\n")
self.html_file.write("<h1>Day: {}</h1>".format(self.day))
ax = pg.Line(height=300,
include_x_axis=True,
label_font_size=2,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
y_title="Energy" + " (kWh)",
legend_at_bottom=True,
x_label_rotation=0)
ax.title = "Energy generated and consumed"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[0],
RENDER_VALUES_dict[RENDER_VALUES_list[0]])
ax.add(RENDER_VALUES_list[1],
RENDER_VALUES_dict[RENDER_VALUES_list[1]])
self.add_content(ax, 1)
ax = pg.Line(height=300,
include_x_axis=True,
label_font_size=1,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
y_title="TCLs SOC",
legend_at_bottom=False,
x_label_rotation=0)
ax.title = "Average TCLs state of charge % and outdoor temperatures"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[2],
RENDER_VALUES_dict[RENDER_VALUES_list[2]])
ax.add(RENDER_VALUES_list[3],
RENDER_VALUES_dict[RENDER_VALUES_list[3]],
secondary=True)
self.add_content(ax, 2)
ax = pg.Line(height=300,
include_x_axis=True,
label_font_size=1,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
spacing=1,
legend_at_bottom=False,
x_label_rotation=0,
style=custom_style)
ax.title = "Retail prices and average consumption from price responsive loads"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[5],
RENDER_VALUES_dict[RENDER_VALUES_list[5]])
ax.add(RENDER_VALUES_list[4],
RENDER_VALUES_dict[RENDER_VALUES_list[4]],
secondary=True)
self.add_content(ax, 3)
ax = pg.Line(height=300,
include_x_axis=True,
label_font_size=1,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
show_legend=False,
x_label_rotation=0,
range=(0, 100))
ax.title = "State of charge of the energy storage system %"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[6],
RENDER_VALUES_dict[RENDER_VALUES_list[6]])
self.add_content(ax, 4)
ax = pg.Bar(height=300,
include_x_axis=True,
label_font_size=2,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
legend_at_bottom=True,
x_label_rotation=0)
ax.title = "Energy sold to and purchased from the main grid (kWh)"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[8],
RENDER_VALUES_dict[RENDER_VALUES_list[8]])
ax.add(RENDER_VALUES_list[7],
RENDER_VALUES_dict[RENDER_VALUES_list[7]])
self.add_content(ax, 5)
ax = pg.Line(height=300,
include_x_axis=True,
label_font_size=2,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
legend_at_bottom=True,
x_label_rotation=0)
ax.title = "Electricity prices in the balancing market (cents/kW)"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[9],
RENDER_VALUES_dict[RENDER_VALUES_list[9]])
ax.add(RENDER_VALUES_list[10],
RENDER_VALUES_dict[RENDER_VALUES_list[10]])
self.add_content(ax, 6)
ax = pg.Bar(height=300,
include_x_axis=True,
label_font_size=2,
truncate_legend=-1,
title_font_size=20,
x_title="Time steps",
legend_at_bottom=True,
x_label_rotation=0)
ax.title = "Energy allocated to and consumed by TCLs (kWh)"
ax.x_labels = range(self.iterations)
ax.add(RENDER_VALUES_list[12],
RENDER_VALUES_dict[RENDER_VALUES_list[12]])
ax.add(RENDER_VALUES_list[11],
RENDER_VALUES_dict[RENDER_VALUES_list[11]])
self.add_content(ax, 7)
self.html_file.write(
"\n <form action=\"\" method=\"post\" novalidate> \n" +
"{{ form.hidden_tag() }} \n " +
"<p>{{ form.next_day() }}</p>\n ")
if self.day != self.day0:
self.html_file.write("<p>{{ form.previous_day() }}</p>\n ")
self.html_file.write(" </form>")
self.html_file.write("{% endblock %}")
self.html_file.close()
reset_dict()
## TO DO: write a render method using pygal
pass
def piechart():
conn = psycopg2.connect(
"dbname='salesdemo' user='******' host='localhost' password='******'"
)
cur1 = conn.cursor()
cur1.execute("""SELECT type, count (type)
FROM public.inventories
group by inventories.type
""")
records = cur1.fetchall()
# print(type(records))
for each in records:
print(each)
ratios = [("Gentlement", 5), ("Ladies", 9)]
pie_chart = pygal.Pie()
pie_chart.title = 'Browser usage in February 2012 (in %)'
pie_chart.add('Products', records[0][1])
pie_chart.add('Others', records[1][1])
pie_chart.add('Services', records[2][1])
# pie_chart.add('Chrome', 36.3)
# pie_chart.add('Safari', 4.5)
# pie_chart.add('Opera', 2.3)
pie_data = pie_chart.render_data_uri()
cur = conn.cursor()
cur.execute(
"""SELECT to_char(to_timestamp(date_part('month',sales.ceated_at)::text,'MM'),'Month') as month, round(sum(inventories.selling_price*sales.quantity))
from public.inventories
join sales on sales.inv_id = inventories.id
group by extract (month from sales.ceated_at)
order by extract (month from sales.ceated_at) asc
""")
rows = cur.fetchall()
# print(type(rows))
months = []
totalsales = []
for each in rows:
months.append(each[0])
totalsales.append(each[1])
print(months)
print(totalsales)
graph = pygal.Line()
graph.title = '% Change Coolness of programming languages over time.'
graph.x_labels = months
graph.add('Total Sales', totalsales)
# graph.add('Java', [15, 45, 76, 80, 91, 95])
# graph.add('C++', [5, 51, 54, 102, 150, 201])
# graph.add('All others combined!', [5, 15, 21, 55, 92, 105])
graph_data = graph.render_data_uri()
return render_template('xyz.html',
pie_data=pie_data,
graph_data=graph_data)
import pygal
import math
filename='btc_close_2017_urllib.json'
with open(filename) as f:
btc_data=json.load(f)
#创建5个列表，分别存储日期和收盘价
dates=[]
months=[]
weeks=[]
weekdays=[]
close=[]
#每天的信息
for btc_dict in btc_data:
dates.append(btc_dict['date'])
months.append(int(btc_dict['month']))
weeks.append(int(btc_dict['week']))
weekdays.append(btc_dict['weekday'])
close.append(int(float(btc_dict['close'])))
#绘制图像
line_chart=pygal.Line(x_label_rotation=20,show_minor_x_labels=False)
line_chart.title="收盘价(¥)"
line_chart.x_labels=dates
N=20 #X坐标每隔20天显示一次
line_chart.x_labels_major=dates[::N]
close_log=[math.log10(_) for _ in close]
line_chart.add("log收盘价",close_log)
line_chart.render_to_file("收盘价折线图(¥).svg")
def queryStockData(symbol, chart_type, time_series, start_date, end_date):
""" Given a set of inputs performs a stock query """
# API Query paramters
series = "TIME_SERIES_" + Constants.TIMESERIES[time_series].upper()
data = {
"function": series,
"symbol": symbol,
"outputsize": "full",
"interval": "60min",
"apikey": Constants.API_KEY
}
print(data)
# Sending our request to the API using the information we put in the data collection.
apiCall = requests.get(Constants.API_URL, params=data)
# Stores the json-enconded content in the retrieved data.
response = apiCall.json()
if (response.__contains__('Note')):
# We hit a throttling limit; just return an error and wait.
return "throttled"
# If statements to change key depending on the Time Serires selected.
if series == "TIME_SERIES_INTRADAY":
timeSeries = "Time Series (60min)"
elif series == "TIME_SERIES_DAILY":
timeSeries = "Time Series (Daily)"
elif series == "TIME_SERIES_WEEKLY":
timeSeries = "Weekly Time Series"
elif series == "TIME_SERIES_MONTHLY":
timeSeries = "Monthly Time Series"
dates = []
opens = []
highs = []
lows = []
closes = []
# Parsing the dates from the user input
startDate = convert_date(start_date)
endDate = convert_date(end_date)
items = list(response[timeSeries].items())
i = len(items) - 1
while i >= 0:
date, stockData = items[i]
# Parsing the date from the api record.
entryDate = convert_date(date)
# Populating lists with data, within the given date range, from API
if (entryDate >= startDate and entryDate <= endDate):
model = StockModel(stockData)
opens.append(model.open)
highs.append(model.high)
lows.append(model.low)
closes.append(model.close)
dates.append(date)
i = i - 1
# If true, prints line chart. Else prints the bar chart.
if (chart_type == "1"):
chart = pygal.Bar(x_label_rotation=45)
else:
chart = pygal.Line(x_label_rotation=45)
chart.x_labels = dates
chart.title = "Stock Date for " + symbol + ": " + start_date + " to " + end_date
chart.add("Open", opens)
chart.add("High", highs)
chart.add("Low", lows)
chart.add("Close", closes)
return chart.render_data_uri()
plt.xlabel('', fontsize=14)
fig.autofmt_xdate()
plt.ylabel('Temp (F)', fontsize=14)
plt.tick_params(axis='both', labelsize=14)
plt.savefig('images/plot_death_valley.png', bbox_inches='tight')
plt.show()
# plt.scatter()
fig = plt.figure(figsize=(10, 6))
plt.scatter(dates, highs, c='red', edgecolors='none', s=10)
plt.scatter(dates, lows, c='blue', edgecolors='none', s=10)
plt.fill_between(dates, highs, lows, facecolor='blue', alpha=.1)
plt.title('Death Valley 2014- highs and lows', fontsize=24)
plt.xlabel('', fontsize=14)
fig.autofmt_xdate()
plt.ylabel('Temp (F)', fontsize=14)
plt.tick_params(axis='both', labelsize=14)
plt.savefig('images/scatter_death_valley.png', bbox_inches='tight')
plt.show()
# pygal.Line()
hist = pygal.Line()
hist.title = 'Death Valley 2014'
hist.x_labels = dates
hist.y_labels = highs
hist.y_labels = lows
hist.add('Highs', highs)
hist.add('Lows', lows)
hist.render_to_file('images/pygal_line_death_valley.svg')
import json
import pygal
with open('data.json') as test_data: #receive data
data = json.load(test_data)
city = {}
remove_case = ["Total (All India)", "Total (States)", "Total (Uts)"]
for year, posit in zip(range(2001, 2013), range(12)):
for i in data:
"""edit year to find 2001-2012 and check requestment"""
if i["State"] not in remove_case and i["Age_group"] != "0-100+" and i["Year"] == year:
"""check in have it dict already or not"""
if i["State"] in city:
city[i["State"]][posit] += i["Total"]
else:
city[i["State"]] = [i["Total"], 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
print("***Complete***") #finish
"""show data process"""
list_city = sorted(list(city))
line_chart = pygal.Line(height=800, width=1000)
line_chart.title = "2001-2012"
line_chart.x_labels = map(str, range(2001, 2013))
for i in list_city:
line_chart.add(i, city[i])
print(i, ":", city[i])
line_chart.render_to_file('2001-2012.svg')
#Get Evaluation Metrics -- MSE, MAE, R2 Score, and Explained Variance Score
print("Model evaluation metrics: ")
print("Test MSE:", mean_squared_error(y_true=y_test, y_pred=preds))
print("Test MAE: ", mean_absolute_error(y_true=y_test, y_pred=preds))
print("Test R2 Score: ", r2_score(y_pred=preds, y_true=y_test))
print("Explained Variance Score: ",
explained_variance_score(y_pred=preds, y_true=y_test))
print("+++++++++++++++++++++++++++++++++++++++")
#Convert Preds and Actual Values on Test Set to Flat List for Plotting
preds_flat = preds.flatten().tolist()
y_test_flat = y_test.flatten().tolist()
#Plot Predictions vs Actual
line_chart = pygal.Line(width=500,
height=300,
explicit_size=True,
x_labels_major_every=150,
show_minor_x_labels=False,
x_label_rotation=45)
line_chart.title = 'Test Predictions vs Actual'
line_chart.x_labels = df['Date'][::-1].iloc[int(0.8 * len(df)):].tolist()
line_chart.add('Preds', preds_flat)
line_chart.add('Actual', y_test_flat)
line_chart.render_in_browser()
# Save Model:
model.save('EUR_USD_1_Day_Forecast_2.h5')
print("Model saved to disk: EUR_USD_1_Day_Forecast_2.h5")
import pygal
chart = pygal.Line(title=u'Some different points')
chart.x_labels = ('one', 'two', 'three')
chart.add('line', [.0002, .0005, .00035])
chart.add('other line', [1000, 2000, 7000], secondary=True)
print(chart.render(is_unicode=True))
import pygal
chart = pygal.Line(fill=True, zero=.0004)
chart.add('line', [.0002, .0005, .00035])
print(chart.render(is_unicode=True))
def plot(start_show, end_show, interval):
try:
conn = http.client.HTTPConnection("")
payload = "temperature=23&token="
headers = {
'content-type': "application/x-www-form-urlencoded",
'x-access-token': "",
'cache-control': "no-cache",
'postman-token': ""
}
if interval == "24":
conn.request("GET", "/api/temperature?unit=hours&count=24",
payload, headers)
smhi_date, smhi_temp = get_smhi('last-days')
smhi_date.pop(0)
smhi_temp.pop(0)
elif interval == 'today':
now = datetime.now()
now = pytz.timezone('UTC').localize(now)
now = now.astimezone(pytz.timezone('Europe/Stockholm'))
nbr_hrs = str(now.hour)
conn.request("GET", "/api/temperature?unit=hours&count=" + nbr_hrs,
payload, headers)
smhi_date, smhi_temp = get_smhi('last-days')
start_time = datetime.now().strftime("%Y-%m-%d 00:00:00")
k = 0
while smhi_date[k] <= str(start_time):
smhi_date.pop(0)
smhi_temp.pop(0)
else:
end_dtg = datetime.strptime(end_show, "%Y-%m-%d %H:%M:%S")
start_dtg = datetime.strptime(start_show, "%Y-%m-%d %H:%M:%S")
delta = end_dtg - start_dtg
nbr_days = str(delta.days)
end_time = end_dtg.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
conn.request(
"GET", "/api/temperature?unit=days&enddate=" + end_time +
"&count=" + nbr_days, payload, headers)
smhi_date, smhi_temp = get_smhi('last-months')
k = 0
while smhi_date[k] < str(start_dtg):
smhi_date.pop(0)
smhi_temp.pop(0)
smhi_temp = map(float, smhi_temp)
res = conn.getresponse()
data = json.loads(res.read().decode('utf-8'))
temp = []
timestamp = []
for x in data['temperatures']:
temp.append(float(x['temperature']))
dtg = datetime.strptime(x['time'], "%Y-%m-%dT%H:%M:%S.%fZ")
dtg = pytz.timezone('UTC').localize(dtg)
dtg = dtg.astimezone(
pytz.timezone('Europe/Stockholm')).replace(tzinfo=None)
dtg = dtg.strftime('%Y-%m-%d %H:%M:%S')
timestamp.append(dtg)
start = datetime.strptime(data['temperatures'][0]['time'],
"%Y-%m-%dT%H:%M:%S.%fZ")
start = pytz.timezone('UTC').localize(start)
start = start.astimezone(
pytz.timezone('Europe/Stockholm')).replace(tzinfo=None)
start = start.strftime('%Y-%m-%d %H:%M:%S')
end = datetime.strptime(
data['temperatures'][len(data['temperatures']) - 1]['time'],
"%Y-%m-%dT%H:%M:%S.%fZ")
end = pytz.timezone('UTC').localize(end)
end = end.astimezone(
pytz.timezone('Europe/Stockholm')).replace(tzinfo=None)
end = end.strftime('%Y-%m-%d %H:%M:%S')
title = 'Temperature in degrees Celsius between ' + start + ' and ' + end
line_chart = pygal.Line(x_label_rotation=30)
line_chart.title = title
if len(temp) < 30:
line_chart.x_labels = map(str, list(timestamp))
line_chart.add('Inside', list(temp))
if interval != 'interval':
line_chart.add('Outside',
list(smhi_temp),
secondary=True,
x_title='Time')
return Response(response=line_chart.render(),
content_type='image/svg+xml')
finally:
conn.close()
import pygal
chart = pygal.Line(truncate_label=-1)
chart.x_labels = [
'This is the first point !',
'This is the second point !',
'This is the third point !',
'This is the fourth point !']
chart.add('line', [0, .0002, .0005, .00035])
print(chart.render(is_unicode=True))
# -*- coding: utf-8 -*-
import pygal
param_line_chart = pygal.Line(interpolate='cubic',
label_font_size=20,
x_label_rotation=50)
param_line_chart.title = 'Parameter Line Chart'
param_line_chart.x_labels = map(str, [
"Data Object 1", "Data Object 2", "Data Object 3", "Data Object 4",
"Data Object 5", "Data Object 6"
])
param_line_chart.add('Data-Set 1', [8, 16, 24, 32, 48, 56])
param_line_chart.add('Data-Set 2', [2, 4, 6, 8, 10, 12])
param_line_chart.add('Data-Set 3', [1, 3, 5, 7, 9, 12])
param_line_chart.render_to_file('lineparam.svg')
custom_style = pygal.style.Style(label_font_size=18,
major_label_font_size=18,
title_font_size=24)
our_css_file = os.path.join(os.path.dirname(__file__), 'pygal.css')
line_chart = pygal.Line(
css=('file://style.css', 'file://graph.css', 'file://' + our_css_file),
background='transparent',
plot_background='transparent',
colors=('#000000', '#888888'),
opacity='1.0',
show_dots=False,
x_label_rotation=1,
x_labels_major_every=HOP_LIMIT // (HOP_STEP * 10),
# legend_at_bottom=True,
# legend_at_bottom_columns=4,
# legend_box_size=24,
# legend_font_size=18,
show_legend=False,
margin=54,
range=(0, 300),
show_minor_x_labels=False,
style=custom_style)
line_chart.title = sys.argv[2]
line_chart.x_title = 'Turnaround time (ms)'
line_chart.y_title = 'Requests count with turnaround time'
line_chart.x_labels = [ttime for ttime in range(0, HOP_LIMIT, HOP_STEP)]
for i, tsv_file in enumerate(sys.argv[3:]):
hop_counts = read_tsv(tsv_file)
def line():
with open('us_exchange_extracted.json', 'r') as data_file:
us_exchange_data = json.load(data_file)
with open('bitcoin_prices.json', 'r') as data_file:
bitcoin_data = json.load(data_file)
with open('ethereum_prices.json', 'r') as data_file:
ethereum_data = json.load(data_file)
custom_style = Style(colors=('#6699ff', '#1cbc7c'),
background='#000000',
plot_background='#1a1a1a',
foreground='#ffffff',
foreground_subtle='#ffffff',
foreground_strong='#ffffff',
legend_font_size=10,
font_family='googlefont:Raleway',
major_label_font_size=7,
label_font_size=8)
chart = pygal.Line(width=600,
height=300,
style=custom_style,
dots_size=0.8,
label_font_size=6,
x_title='Time',
y_title='Price',
x_labels_major_every=300,
y_labels_major_every=None,
x_label_rotation=20,
show_minor_x_labels=False)
chart.title = 'Exchange rates of US Dollar'
coin_chart = pygal.Line(width=600,
height=300,
style=custom_style,
dots_size=0.8,
label_font_size=10,
x_title='Time',
y_title='Price',
x_labels_major_every=200,
y_labels_major_every=None,
x_label_rotation=20,
show_minor_x_labels=False)
coin_chart.title = 'Prices of coins'
francs_list = []
for x in us_exchange_data:
temp = {'value': x['FRANCS/US$'], 'label': x['YEAR']}
francs_list.append(temp)
chart.add('Francs/USD', francs_list)
singapore_list = []
for x in us_exchange_data:
temp = {'value': x['SINGAPORE/US$'], 'label': x['YEAR']}
singapore_list.append(temp)
chart.add('Singapore/USD', singapore_list)
kroner_list = []
for x in us_exchange_data:
temp = {'value': x['KRONER/US$'], 'label': x['YEAR']}
kroner_list.append(temp)
chart.add('Kroner/USD', kroner_list)
ethereum_list = []
for x in ethereum_data:
temp = {'value': x['Open'], 'label': x['Date']}
ethereum_list.append(temp)
ethereum_list.reverse()
coin_chart.add('Ethereum', (ethereum_list))
coin_chart.x_labels = [x['label'] for x in ethereum_list]
bitcoin_list = []
for x in bitcoin_data:
temp = {'value': x['Open'], 'label': x['Date']}
bitcoin_list.append(temp)
bitcoin_list.reverse()
coin_chart.add('Bitcoin', (bitcoin_list))
chart.x_labels = [x['YEAR'] for x in us_exchange_data]
coin_chart.render_to_file('static/images/coin_line_chart.svg')
chart.render_to_file('static/images/line_chart.svg')
img_url = 'static/images/line_chart.svg?cache=' + str(time.time())
coin_url = 'static/images/coin_line_chart.svg?cache=' + str(time.time())
return render_template('line_chart.html',
image_url=img_url,
coin_chart=coin_url)
def data_visualisation():
conn = psycopg2.connect(
" dbname='inventory_management_system' user='******' host='localhost' port='5432' password='******' "
)
cur = conn.cursor()
cur.execute("""
SELECT type, count(type)
FROM public.inventories
group by type;
""")
product_service = cur.fetchall()
print(product_service)
pie_chart = pygal.Pie()
'''my_pie_data = [
('Nairobi', 63),
('Mombasa', 20),
('Kilifi', 17),
('Machakos', 30),
('Kiambu', 7)]'''
pie_chart.title = 'Ratio of product and service'
for each in product_service:
pie_chart.add(each[0], each[1])
pie_data = pie_chart.render_data_uri()
#end of pie chart
#start of line graph
cur.execute("""
SELECT EXTRACT(MONTH FROM s.created_at) as sales_month, sum(quantity*selling_price) as total_sales
from sales as s
join inventories as i on s.invid = i.id
group by sales_month
order by sales_month asc;
""")
monthly_sales = cur.fetchall()
print(monthly_sales)
data = [{
'month': 'January',
'total': 22
}, {
'month': 'February',
'total': 27
}, {
'month': 'March',
'total': 23
}, {
'month': 'April',
'total': 20
}, {
'month': 'May',
'total': 12
}, {
'month': 'June',
'total': 32
}, {
'month': 'July',
'total': 42
}, {
'month': 'August',
'total': 72
}, {
'month': 'September',
'total': 52
}, {
'month': 'October',
'total': 42
}, {
'month': 'November',
'total': 92
}, {
'month': 'December',
'total': 102
}]
a = []
b = []
for each in monthly_sales:
a.append(each[0])
b.append(each[1])
line_chart = pygal.Line()
line_chart.title = 'Total Sales in the year 2019'
line_chart.x_labels = a
line_chart.add('Total Sales', b)
line_data = line_chart.render_data_uri()
return render_template('chart.html', pie=pie_data, line=line_data)
import pygal
chart = pygal.Line(inverse_y_axis=True)
chart.add('line', [.0002, .0005, .00035])
print(chart.render(is_unicode=True))
else:
highStr = ""
highStr = highStr.join(temhigh)
highs.append(int(highStr)) # 以上三行将高温NavigableString转成int类型并存入高温列表
temp.append(temperate)
final.append(temp)
i = i + 1
# 将最终的获取的天气写入csv文件
with open('weather.csv', 'a', errors='ignore', newline='') as f:
f_csv = csv.writer(f)
f_csv.writerows([cityname])
f_csv.writerows(final)
# 绘图
bar = pygal.Line() # 创建折线图
bar.add('最低气温', lows)
bar.add('最高气温', highs)
bar.x_labels = daytimes
bar.x_labels_major = daytimes[::30]
# bar.show_minor_x_labels = False # 不显示X轴最小刻度
bar.x_label_rotation = 45
bar.title = cityname+'未来七天气温走向图'
bar.x_title = '日期'
bar.y_title = '气温(摄氏度)'
bar.legend_at_bottom = True
bar.show_x_guides = False
# coding=utf-8
foreground_dark='rgba(0, 0, 0, 0.3)',
colors=('rgb(163, 190, 140)',
'rgb(123, 163, 168)',
'rgb(130, 192, 175)',
'rgb(159, 224, 246)',
'rgb(0, 146, 199)',
'rgb(91, 144, 191)',
'rgb(40, 81, 113)',
'rgb(190, 173, 146)',
'rgb(243, 90, 74)',
'rgb(91, 73, 71)',
'rgb(218, 145, 122)',
'rgb(242, 156, 156)')
)
line = pygal.Line(
width=800, height=400, interpolate='hermite', style=custom_style)
line.title = u'每月种子下载平均量统计'
line.x_labels = [u'1月', u'2月', u'3月', u'4月', u'5月',
u'6月', u'7月', u'8月', u'9月', u'10月', u'11月', u'12月']
line.add(u'2012年', h.monthes(2012, None))
line.add(u'2013年', h.monthes(2013, None))
line.add(u'2014年', h.monthes(2014, None))
line.render_to_file(hsvgpath + 'month_ave.svg')
line = pygal.Line(
width=800, height=400, interpolate='hermite', style=custom_style)
line.title = u'每月种子下载累积量统计'
line.x_labels = [u'起始', u'1月', u'2月', u'3月', u'4月', u'5月',
u'6月', u'7月', u'8月', u'9月', u'10月', u'11月', u'12月']
line.add(u'2012年', h.accum(h.monthes(2012)))
line.add(u'2013年', h.accum(h.monthes(2013)))
def words_usage(self, event, word, unit='days', amount=7):
sql = '''
SELECT date, coalesce(count, 0) AS count
FROM
generate_series(
NOW() - interval %s,
NOW(),
%s
) AS date
LEFT OUTER JOIN (
SELECT date_trunc(%s, timestamp) AS dt, count(*) AS count
FROM messages
WHERE
timestamp >= (NOW() - interval %s) AND
timestamp < (NOW()) AND
guild_id=%s AND
(SELECT count(*) FROM regexp_matches(content, %s)) >= 1
GROUP BY dt
) results
ON (date_trunc(%s, date) = results.dt);
'''
msg = event.msg.reply(':alarm_clock: One moment pls...')
start = time.time()
tuples = list(Message.raw(
sql,
'{} {}'.format(amount, unit),
'1 {}'.format(unit),
unit,
'{} {}'.format(amount, unit),
event.guild.id,
'\s?{}\s?'.format(word),
unit
).tuples())
sql_duration = time.time() - start
start = time.time()
chart = pygal.Line(style=pygal.style.NeonStyle)
chart.title = 'Usage of {} Over {} {}'.format(
word, amount, unit,
)
if unit == 'days':
chart.x_labels = [i[0].strftime('%a %d') for i in tuples]
elif unit == 'minutes':
chart.x_labels = [i[0].strftime('%X') for i in tuples]
else:
chart.x_labels = [i[0].strftime('%x %X') for i in tuples]
chart.x_labels = [i[0] for i in tuples]
chart.add(word, [i[1] for i in tuples])
pngdata = cairosvg.svg2png(
bytestring=chart.render(),
dpi=72)
chart_duration = time.time() - start
event.msg.reply(
'_SQL: {}ms_ - _Chart: {}ms_'.format(
int(sql_duration * 1000),
int(chart_duration * 1000),
),
attachments=[('chart.png', pngdata)])
msg.delete()
# Dimensions
IN_SIZE = 1000
HIDDEN_SIZE = 100
OUT_SIZE = 10
NO_OF_EXAMPLES = 64
LEARNING_RATE = 1e-4
# Input and Output Data ( Here we choose some random input and output to train with)
X = Variable(torch.randn(NO_OF_EXAMPLES, IN_SIZE).type(dtype))
Y = Variable(torch.randn(NO_OF_EXAMPLES, OUT_SIZE).type(dtype),
requires_grad=False)
# For Graphs
loss_vals = []
line_graph = pygal.Line()
line_graph.title = 'Loss'
model = torch.nn.Sequential(torch.nn.Linear(IN_SIZE, HIDDEN_SIZE),
torch.nn.ReLU(),
torch.nn.Linear(HIDDEN_SIZE, OUT_SIZE))
loss_func = torch.nn.MSELoss(size_average=False)
for episode in range(500):
# Calculate Y_predict
Y_pred = model(X)
loss = loss_func(Y_pred, Y)
loss_vals.append(loss.data[0])
print("Episode : {} \t Loss = {}".format(episode, loss))
#Import modules
def make_graph(graph_style):
msg = ""
graph_data = ""
rv = ran.randint(3, 60)
try:
if graph_style == "Line":
graph = pygal.Line(fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
graph.title = "Timeline year soda sales in mil"
graph.x_labels = ["2000", "2001", "2003", "2004", "2005"]
graph.add("Pepsi", [rv, rv + 20, rv - 5, rv + 3, rv + 12])
graph.add("Coca Cola", [rv + 5, rv + 18, rv - 5, rv + 20, rv + 25])
graph.add("Sprite", [rv, rv + 6, rv - 9, rv + 5, rv + 12])
graph.add("Orange", [rv + 4, rv + 30, rv - 10, rv, rv + 8])
graph_data = graph.render_data_uri()
msg = "Line"
elif graph_style == "Bar":
graph = pygal.Bar(fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
graph.title = "Timeline year soda sales in mil"
graph.x_labels = ["2000", "2001", "2003", "2004", "2005"]
graph.add("Pepsi", [rv, rv + 20, rv - 5, rv + 3, rv + 12])
graph.add("Coca Cola", [rv + 5, rv + 18, rv - 5, rv + 20, rv + 25])
graph.add("Sprite", [rv, rv + 6, rv - 9, rv + 5, rv + 12])
graph.add("Orange", [rv + 4, rv + 30, rv - 10, rv, rv + 8])
graph_data = graph.render_data_uri()
msg = "Bar"
elif graph_style == "Treemap":
treemap = pygal.Treemap(fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
treemap.title = 'Binary TreeMap'
treemap.add('A', [2, 1, 12, 4, 2, 1, 1, 3, 12, 3, 4, None, 9])
treemap.add('B', [4, 2, 5, 10, 3, 4, 2, 7, 4, -10, None, 8, 3, 1])
treemap.add('C', [3, 8, 3, 3, 5, 3, 3, 5, 4, 12])
treemap.add('D', [23, 18])
treemap.add('E',
[1, 2, 1, 2, 3, 3, 1, 2, 3, 4, 3, 1, 2, 1, 1, 1, 1, 1])
treemap.add('F', [31])
treemap.add('G', [5, 9.3, 8.1, 12, 4, 3, 2])
treemap.add('H', [12, 3, 3])
graph_data = treemap.render_data_uri()
msg = " Treemap"
elif graph_style == "Gauge":
gauge_chart = pygal.Gauge(human_readable=True,
fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
gauge_chart.title = 'DeltaBlue V8 benchmark results'
gauge_chart.range = [0, 10000]
gauge_chart.add('Chrome', 8212)
gauge_chart.add('Firefox', 8099)
gauge_chart.add('Opera', 2933)
gauge_chart.add('IE', 41)
graph_data = gauge_chart.render_data_uri()
msg = "Gauge"
elif graph_style == "SolidGauge":
gauge = pygal.SolidGauge(inner_radius=0.70,
fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
percent_formatter = lambda x: '{:.10g}%'.format(x)
dollar_formatter = lambda x: '{:.10g}$'.format(x)
gauge.value_formatter = percent_formatter
gauge.add('Series 1', [{
'value': 225000,
'max_value': 1275000
}],
formatter=dollar_formatter)
gauge.add('Series 2', [{'value': 110, 'max_value': 100}])
gauge.add('Series 3', [{'value': 50}])
gauge.add('Series 4', [{
'value': 51,
'max_value': 100
}, {
'value': 12,
'max_value': 100
}])
gauge.add('Series 5', [{'value': 79, 'max_value': 100}])
gauge.add('Series 6', 99)
gauge.add('Series 7', [{'value': 100, 'max_value': 100}])
graph_data = gauge.render_data_uri()
msg = "SolidGauge"
elif graph_style == "XY":
xy_chart = pygal.XY(fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
xy_chart.title = 'XY Cosinus'
xy_chart.add('x = cos(y)',
[(cos(x / 10.), x / 10.) for x in range(-50, 50, 5)])
xy_chart.add('y = cos(x)',
[(x / 10., cos(x / 10.)) for x in range(-50, 50, 5)])
xy_chart.add('x = 1', [(1, -5), (1, 5)])
xy_chart.add('x = -1', [(-1, -5), (-1, 5)])
xy_chart.add('y = 1', [(-5, 1), (5, 1)])
xy_chart.add('y = -1', [(-5, -1), (5, -1)])
graph_data = xy_chart.render_data_uri()
msg = "XY"
elif graph_style == "Multi-series pie":
pie_chart = pygal.Pie(fill=True,
interpolate='cubic',
style=DarkColorizedStyle)
pie_chart.title = 'Browser usage by version in February 2012 (in %)'
pie_chart.add('IE', [5.7, 10.2, 2.6, 1])
pie_chart.add('Firefox',
[.6, 16.8, 7.4, 2.2, 1.2, 1, 1, 1.1, 4.3, 1])
pie_chart.add('Chrome', [.3, .9, 17.1, 15.3, .6, .5, 1.6])
pie_chart.add('Safari', [4.4, .1])
pie_chart.add('Opera', [.1, 1.6, .1, .5])
graph_data = pie_chart.render_data_uri()
msg = "Multi-series pie"
except Exception as e:
msg = e
t = (msg, graph_data)
return t
def piechart():
conn = psycopg2.connect("dbname='sales_demo' user='******' host='localhost' password='******' ")
ratios = [('Gentlemen', 5), ('Ladies',9)]
# ratios[0][0]
# ratios1 = [{},{}]
pie_chart = pygal.Pie()
pie_chart.title = 'Browser usage in February 2012 (in %)'
pie_chart.add(ratios[0][0], ratios[0][1])
pie_chart.add(ratios[1][0], ratios[1][1])
# pie_chart.add('Chrome', 36.3)
# pie_chart.add('Safari', 4.5)
# pie_chart.add('Opera', 2.3)
pie_data = pie_chart.render_data_uri()
data = [
{'month': 'January', 'total': 22},
{'month': 'February', 'total': 27},
{'month': 'March', 'total': 23},
{'month': 'April', 'total': 20},
{'month': 'May', 'total': 12},
{'month': 'June', 'total': 32},
{'month': 'July', 'total': 42},
{'month': 'August', 'total': 72},
{'month': 'September', 'total': 52},
{'month': 'October', 'total': 42},
{'month': 'November', 'total': 92},
{'month': 'December', 'total': 102}
]
cur = conn.cursor()
# cur.execute("""SELECT (sum(i.selling_price * s.quatity)) as subtotal, EXTRACT(MONTH FROM s.created_at) as sales_month
# from sales as s
# join inventories as i on s.inv_id = i.id
# GROUP BY sales_month
# ORDER BY sales_month
# """)
#
rows = cur.fetchall()
# # print(type(rows))
months = []
total_sales = []
for each in rows:
months.append(each[1])
total_sales.append(each[0])
#
# print(months)
# print(total_sales)
graph = pygal.Line()
graph.title = '% Change Coolness of programming languages over time.'
graph.x_labels = months
graph.add('Total Sales', total_sales)
# graph.add('Java', [15, 45, 76, 80, 91, 95])
# graph.add('C++', [5, 51, 54, 102, 150, 201])
# graph.add('All others combined!', [5, 15, 21, 55, 92, 105])
graph_data = graph.render_data_uri()
# return render_template("graphing.html", graph_data=graph_data)
return render_template('index.html', pie_data=pie_data, graph_data=graph_data)
def home():
# print ("__xlabels__",var_x_labels)
#####################################Active session chart #####
custom_style = Style(colors=('#351508', '#404040', '#9BC850'))
title = 'STB Uptime'
bar_chart = pygal.Bar(width=400,
height=400,
explicit_size=True,
title=title,
x_label_rotation=90,
style=custom_style)
var_x_labels = []
var_data = []
for idx1 in list(range(0, len(data_time_spent))):
var_end_time = datetime.utcfromtimestamp(
int(data_time_spent.Date_Time[idx1])).strftime('%Y-%m-%d %H:%M:%S')
var_x_labels.append(var_end_time)
var_data.append(data_time_spent.Time_spent[idx1])
# print(data_time_spent.Time[idx1])
bar_chart.x_labels = var_x_labels
var_time_spent = var_data
bar_chart.add('Active session time', var_time_spent)
bar_chart.render_to_file('static/images/bar_chart.svg')
#####################################Active session line chart #####
line_chart = pygal.Line()
line_chart.title = 'Time series'
# line_chart.x_labels = map(
# date.isoformat,
# rrule(DAILY, dtstart=date(2010, 8, 1), until=date.today())
# )
# line_chart.y_labels = map(str,range(1,25))
var_date_series = []
var_start_time_series = []
var_end_time_series = []
var_time_series_plot = []
for idx1 in list(range(0, len(data_time_spent))):
tmp_start_time = data_time_spent.Date_Time[
idx1] - data_time_spent.Time_spent[idx1]
var_date_series.append(
datetime.utcfromtimestamp(
int(tmp_start_time)).strftime('%Y-%m-%d'))
var_start_time_series.append(
datetime.utcfromtimestamp(
int(tmp_start_time)).strftime('%H:%M:%S'))
var_end_time_series.append(
datetime.utcfromtimestamp(int(
data_time_spent.Date_Time[idx1])).strftime('%H:%M:%S'))
line_chart.x_labels = var_date_series
line_chart.x_labels = map(str, range(2002, 2013))
print("##########var date series####", var_date_series)
print("##########var start time series####", var_start_time_series)
print("##########var end time series####", var_end_time_series)
line_chart.add("start Time", [12, 34, 10, 5, 7])
line_chart.add("End Time", [22, 12, 13, 16, 5])
line_chart.render_to_file('static/images/line_chart.svg')
################################### Avg time spent chart #######
title2 = 'Avg time spent on each screen'
custom_style = Style(colors=('#059467', '#9BC850', '#E80080'))
avg_bar_chart = pygal.Bar(width=1200,
height=800,
explicit_size=True,
title=title2,
x_label_rotation=70,
style=custom_style)
var_x_labels = []
var_data = []
# print ("__xlabels__",var_x_labels)
# print ("avg time spent===",avg_time_spent)
for idx1 in list(range(0, len(avg_time_spent))):
var_x_labels.append(avg_time_spent.Screen_id[idx1])
var_data.append(avg_time_spent.Avg_Time[idx1])
# print(avg_time_spent.Avg_Time[idx1])
avg_bar_chart.x_labels = var_x_labels
# bar_chart.y_labels = var_y_labels
# var_time_spent = [data_time_spent[x] for x in data_time_spent]
# print ("_Time spent_",var_time_spent)
# print ("_Time spent_0___",var_time_spent[0])
# print ("_Time spent_1___",var_time_spent[1])
var_time_spent = var_data
avg_bar_chart.add('Avg time sec', var_data)
avg_bar_chart.render_to_file('static/images/screen_avg_chart.svg')
###################################
title2 = 'Least used screens'
custom_style = Style(colors=('#1878f7', '#404040', '#E80080'))
avg_bar_chart = pygal.Bar(width=1200,
height=600,
explicit_size=True,
title=title2,
x_label_rotation=90,
style=custom_style)
var_x_labels = []
var_data = []
# print ("__xlabels__",var_x_labels)
for idx1 in list(range(0, len(data_tf_idf))):
var_x_labels.append(data_tf_idf.GUI[idx1])
var_data.append(data_tf_idf.Priority[idx1])
# print(avg_time_spent.Avg_Time[idx1])
avg_bar_chart.x_labels = var_x_labels
# bar_chart.y_labels = var_y_labels
# var_time_spent = [data_tf_idf[x] for x in data_tf_idf]
# print ("_Time spent_",var_time_spent)
# print ("_Time spent_0___",var_time_spent[0])
# print ("_Time spent_1___",var_time_spent[1])
var_time_spent = var_data
avg_bar_chart.add('Least used screen', var_time_spent)
avg_bar_chart.render_to_file('static/images/tf_idf_chart.svg')
#====================Donut chart of the screens used==================
pie_chart = pygal.Pie(width=1200,
height=600,
explicit_size=True,
inner_radius=.2)
pie_chart.title = 'Time spent on each screen (in %)'
var_x_labels = []
var_data = []
total_values = 0
for idx1 in list(range(0, len(avg_time_spent))):
total_values = total_values + avg_time_spent.Avg_Time[idx1]
# print ("Total value===",total_values)
for idx1 in list(range(0, len(avg_time_spent))):
prcnt = round((avg_time_spent.Avg_Time[idx1] / total_values) * 100, 2)
# print ("% = ",prcnt)
pie_chart.add(avg_time_spent.Screen_id[idx1], prcnt)
pie_chart.render_to_file('static/images/donut.svg')
#==================================Gauge chart==========
gauge = pygal.SolidGauge(inner_radius=0.70)
percent_formatter = lambda x: '{:.10g}%'.format(x)
gauge.value_formatter = percent_formatter
#====Screen Pattern Table Info=====================================
for idx in list(range(0, len(avg_time_spent))):
# print (idx,"=>",avg_time_spent.Screen_id[idx])
for idx2 in list(range(0, len(var_full_data))):
if (avg_time_spent.Screen_id[idx] == var_full_data.ScreenName[idx2]
):
# print (idx2,"count=",var_full_data.ScreenName[idx2])
if (idx2 + 1 >= len(var_full_data)):
continue
else:
var_screen_id_dict[avg_time_spent.Screen_id[idx]].append(
var_full_data.ScreenName[idx2 + 1])
# print("screneid =",avg_time_spent.Screen_id[idx],"next id=",var_full_data.ScreenName[idx2+1])
# print("The next screen list stored==========")
# print (var_screen_id_dict)
#====scatter plot=====================================
# xy_chart = pygal.XY(width=1200,height=600,explicit_size=True,stroke=False)
# xy_chart.title = 'Scatter plot of the screen ID and time spent'
# xy_chart.add('2', [(.1, .15), (.12, .23), (.4, .3), (.6, .4), (.21, .21), (.5, .3), (.6, .8), (.7, .8)])
# xy_chart.add('3', [(.05, .01), (.13, .02), (1.5, 1.7), (1.52, 1.6), (1.8, 1.63), (1.5, 1.82), (1.7, 1.23), (2.1, 2.23), (2.3, 1.98)])
# xy_chart.render_to_file('static/images/scatter.svg')
#======================================
my_html = create_html_page()
return my_html
# -*- coding: utf-8 -*-
import pygal
param_line_chart = pygal.Line(fill=True, label_font_size=20)
param_line_chart.title = 'Parameter Line Chart'
param_line_chart.x_labels = map(str, [
"Data Object 1", "Data Object 2", "Data Object 3", "Data Object 4",
"Data Object 5", "Data Object 6"
])
param_line_chart.add('Data-Set 1', [8, 16, 24, 32, 48, 56])
param_line_chart.add('Data-Set 2', [2, 4, 6, 8, 10, 12])
param_line_chart.add('Data-Set 3', [1, 3, 5, 7, 9, 12])
param_line_chart.render_to_file('lineparam.svg')
def scatter():
with open('bitcoin_prices.json', 'r') as data_file:
bitcoin_data = json.load(data_file)
with open('ethereum_prices.json', 'r') as data_file:
ethereum_data = json.load(data_file)
with open('litecoin_prices.json', 'r') as data_file:
litecoin_data = json.load(data_file)
with open('monero_prices.json', 'r') as data_file:
monero_data = json.load(data_file)
with open('dash_prices.json', 'r') as data_file:
dash_data = json.load(data_file)
with open('iota_prices.json', 'r') as data_file:
iota_data = json.load(data_file)
with open('nem_prices.json', 'r') as data_file:
nem_data = json.load(data_file)
with open('omisego_prices.json', 'r') as data_file:
omisego_data = json.load(data_file)
with open('qtum_prices.json', 'r') as data_file:
qtum_data = json.load(data_file)
with open('stratis_prices.json', 'r') as data_file:
stratis_data = json.load(data_file)
with open('waves_prices.json', 'r') as data_file:
waves_data = json.load(data_file)
custom_style = Style(colors=('#E853A0', '#E8537A', '#E95355', '#E87653',
'#E89B53'),
background='#000000',
plot_background='#1a1a1a',
foreground='#ffffff',
foreground_subtle='#ffffff',
foreground_strong='#ffffff',
legend_font_size=10,
font_family='googlefont:Raleway',
major_label_font_size=7,
label_font_size=8)
chart = pygal.Line(width=600,
height=300,
style=custom_style,
dots_size=0.2,
label_font_size=6,
x_title='Time',
y_title='Price',
y_labels_major_every=None,
x_label_rotation=20,
show_minor_x_labels=False,
stroke=False)
chart.title = 'Comparison of lesser known coins'
bitcoin_list = []
for x in bitcoin_data:
temp = {'value': x['Open'] / 100, 'label': x['Date']}
bitcoin_list.append(temp)
bitcoin_list.reverse()
chart.add('Bitcoin/100', bitcoin_list)
nem_list = [x['Open'] for x in nem_data]
# nem_list = []
# for x in nem_data:
# temp = {
# 'value': x['Open'],
# 'label': x['Date']
# }
nem_list.reverse()
chart.add('Nem', nem_list)
stratis_list = [x['Open'] for x in stratis_data]
# stratis_list = []
# for x in stratis_data:
# temp = {
# 'value': x['Open'],
# 'label': x['Date']
# }
stratis_list.reverse()
chart.add('Stratis', stratis_list)
waves_list = [x['Open'] for x in waves_data]
# waves_list = []
# for x in waves_data:
# temp = {
# 'value': x['Open'],
# 'label': x['Date']
# }
waves_list.reverse()
chart.add('Waves', waves_list)
iota_list = [x['Open'] for x in iota_data]
# iota_list = []
# for x in iota_data:
# temp = {
# 'value': x['Open'],
# 'label': x['Date']
# }
iota_list.reverse()
chart.add('Iota', iota_list)
label_list = []
for x in nem_data:
temp = {'value': x['Open'], 'label': x['Date']}
label_list.append(temp)
label_list.reverse()
chart.x_labels = [x['label'] for x in label_list]
chart.render_to_file('static/images/scatter_chart.svg')
img_url = 'static/images/scatter_chart.svg?cache=' + str(time.time())
return render_template('template.html', image_url=img_url)
import pygal
chart = pygal.Line()
chart.add('line', [.0002, .0005, .00035], show_dots=False)
chart.add('line', [.0004, .0009, .001])
print(chart.render(is_unicode=True))
def data_visualization():
'''
Add components to your pie chart
1. add title
2. Partition your pie chart
'''
cur.execute("""
SELECT type, count(type)
FROM public.inventories
GROUP BY type;
""")
product_service = cur.fetchall()
# print(product_service)
# Initialize your pie chart
pie_chart = pygal.Pie()
# my_pie_data = [
# ('Nairobi', 63),
# ('Mombasa', 20),
# ('Kilifi', 17),
# ('Machakos', 30),
# ('Kiambu', 7)
# ]
pie_chart.title = 'Ratio of product and service'
for each in product_service:
pie_chart.add(each[0], each[1])
# pie_chart.add('Nairobi', 63)
# pie_chart.add('Mombasa', 20)
# pie_chart.add('Kilifi', 17)
# pie_chart.add('Machakos', 30)
# pie_chart.add('Kiambu', 7)
pie_data = pie_chart.render_data_uri()
# end of piechart
# start of line graph
# represennts sales made in every month
cur.execute("""
SELECT EXTRACT(MONTH FROM s.created_at) as sales_month, sum(quantity * selling_price) as total_sales
from sales as s
join inventories as i on s.inv_id = i.id
GROUP BY sales_month
ORDER BY sales_month
""")
monthly_sales=cur.fetchall()
# print(monthly_sales)
data = [
{'month': 'January', 'total': 22},
{'month': 'February', 'total': 27},
{'month': 'March', 'total': 23},
{'month': 'April', 'total': 20},
{'month': 'May', 'total': 12},
{'month': 'June', 'total': 32},
{'month': 'July', 'total': 42},
{'month': 'August', 'total': 72},
{'month': 'September', 'total': 52},
{'month': 'October', 'total': 42},
{'month': 'November', 'total': 92},
{'month': 'December', 'total': 102}
]
x = []
sales = []
for each in monthly_sales:
x.append(each[0])
sales.append(each[1])
# print(x)
# print(sales)
line_graph = pygal.Line()
line_graph.title = 'Total sales made in every month in the year 2019'
line_graph.x_labels = map(str, x)
# line_graph.add('Firefox', [None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1, 42.8])
# line_graph.add('Chrome', [None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3, 23.8])
# line_graph.add('IE', [85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1, 26.6])
# line_graph.add('Others', [14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5, 26.6])
line_graph.add('Total Sales', sales)
line_data = line_graph.render_data_uri()
'''
x = "tech"
y = x
y = x = 'tech'
'''
return render_template('charts.html', pie=pie_data, line=line_data)
