def generalview():
# Create general overview
now = dt.datetime.now()
lastmonthmonth = now.month - 1
lastmonthyear = now.year
trans_data_dict = dbc.getgeneral()
# Changes dictionary items to key = [last month amount, total amount, mean amount per month, std per month]
for key, value in trans_data_dict.iteritems():
vdate, vamount = zip(*value)
total_amount = np.sum(vamount)
month_amount = 0
my_array = []
my_amounts = []
for i in range(len(vdate)):
date = dt.datetime.strptime(vdate[i], "%Y-%m-%dT%H:%M:%S")
dmonth = date.month
dyear = date.year
monyear_string = str(dmonth) + str(dyear)
# Sums for each month -> find mean spend per month.
if monyear_string not in my_array:
my_array.append(monyear_string)
my_amounts.append(vamount[i])
else:
my_ind = my_array.index(monyear_string)
my_amounts[my_ind] += vamount[i]
# Sums spending for last month
if dmonth == lastmonthmonth and dyear == lastmonthyear:
month_amount += vamount[i]
mean_pm = np.mean(my_amounts)
me_pm = np.std(my_amounts) / len(my_amounts)
trans_data_dict[key] = [abs(month_amount), abs(total_amount), abs(mean_pm), me_pm]
# Making Bar Chart
labels = [] # list of all keys
mspend = [] # list of monthly spend for each key
tspend = [] # list of total spend for each key
mean_spend = [] # list of mean monthly spend for each key
me_ms = [] # list of error on mean
m_in = 0 # monthly money in
t_in = 0 # total money in
for key, values in trans_data_dict.iteritems():
if key != "Money In":
labels.append(key)
mspend.append(values[0])
tspend.append(values[1])
mean_spend.append(values[2])
me_ms.append(values[3])
else:
m_in = values[0]
t_in = values[1]
fig, axarr = plt.subplots(1, 2)
ind = np.arange(len(labels)) # index for each label
width = 0.8 # width of bar
rot = 75 # Angle of text (x-axis)
axarr[0].bar(ind, mspend, color="red")
axarr[0].errorbar(ind + (width / 2), mean_spend, yerr=me_ms, fmt="o")
axarr[0].set_xticks(ind + (width / 2))
axarr[0].set_xticklabels(labels, rotation=rot)
axarr[0].set_ylabel("Amount Spent DKK")
axarr[0].set_title(
"Last Month (%d/%d) - Compared to Mean\n(Net In: %.2f DKK)"
% (lastmonthmonth, lastmonthyear, m_in - np.sum(mspend))
)
axarr[1].bar(ind, tspend, color="green")
axarr[1].set_xticks(ind + (width / 2))
axarr[1].set_xticklabels(labels, rotation=rot)
axarr[1].set_ylabel("Amount Spent DKK")
axarr[1].set_title("Total Spending \n(Net In: %.2f DKK)" % (t_in - np.sum(tspend)))
plt.suptitle("Where Money is Spent")
plt.show()
return
def dayview():
"""
Plots a bar chart showing the spending per type of transaction per day.
:return:
"""
trans_data_dict = dbc.getgeneral()
# Changes dictionary items to key = [monday_spend, tuesday_spend, wednesday_spend, etc.]
for key, value in trans_data_dict.iteritems():
vdate, vamount = zip(*value)
mon_sum = 0
tue_sum = 0
wed_sum = 0
thu_sum = 0
fri_sum = 0
sat_sum = 0
sun_sum = 0
for i in range(len(vdate)):
date = dt.datetime.strptime(vdate[i], "%Y-%m-%dT%H:%M:%S")
if date.weekday() == 0:
mon_sum += vamount[i]
elif date.weekday() == 1:
tue_sum += vamount[i]
elif date.weekday() == 2:
wed_sum += vamount[i]
elif date.weekday() == 3:
thu_sum += vamount[i]
elif date.weekday() == 4:
fri_sum += vamount[i]
elif date.weekday() == 5:
sat_sum += vamount[i]
elif date.weekday() == 6:
sun_sum += vamount[i]
trans_data_dict[key] = [
abs(mon_sum),
abs(tue_sum),
abs(wed_sum),
abs(thu_sum),
abs(fri_sum),
abs(sat_sum),
abs(sun_sum),
]
# Variables needed for graph
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"] # x-axis tick labels
no_of_types = len(trans_data_dict.keys()) # number of transaction types
ind = np.arange(len(days)) # index
day_width = 0.95 # so that there is a gap between days
width = day_width / no_of_types # width of each type's bar
colours = iter(cm.rainbow(np.linspace(0, 1, no_of_types))) # Allows to automatically assign colours
rot = 0 # Angle of text (x-axis)
count = 0
# Plotting
ax = plt.subplot(111)
for key, values in trans_data_dict.iteritems():
if key != "Money In":
ax.bar(ind + (count * width), values / np.sum(values), width, color=next(colours), label=key)
count += 1
ax.set_xticks(ind + (day_width / 2))
ax.set_xticklabels(days, rotation=rot)
ax.set_xlabel("Day of the Week")
ax.set_ylabel("Normalised Spending")
ax.set_title("Comparison Of Spending Type Per Day")
# Shrink plot width to put legend outside
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.95, box.height])
plt.legend(loc="center left", bbox_to_anchor=(1, 0.5))
plt.grid(b=True, which="major")
plt.show()
return
