def make_hot_plot(data, p_id):
"""
根据评价最近评价来判断这个产品是否是热门
:param datas:
:return:
"""
if data:
data = data.split(",")
dt1 = datetime.datetime.now()
temp = list(set(data))
sub_dates = [(dt1 - datetime.datetime.strptime(dt, '%Y-%m-%d')).days
for dt in temp]
actives = []
for d in sub_dates:
if d <= 360:
actives.append(100)
elif 360 < d <= 500:
actives.append(60)
else:
actives.append(0)
date_dict = {'sub_date': sub_dates, 'active': actives}
df = pd.DataFrame(date_dict, index=temp)
df.plot(subplots=True)
plt.savefig("static/upload/%s_h.png" % p_id, dpi=90)
return file_hepler.get_image_path("%s_h.png" % p_id)
else:
return file_hepler.get_image_path("no_hot.png")
def make_hot_bokeh(data):
from bokeh.models import BoxAnnotation
if data:
data = data.split(",")
dt1 = datetime.datetime.now()
temp = list(set(data))
sub_dates = [(dt1 - datetime.datetime.strptime(dt, '%Y-%m-%d')).days
for dt in temp]
s = pd.Series(
sub_dates,
[datetime.datetime.strptime(dt, '%Y-%m-%d') for dt in temp])
s = s.sort_index(ascending=False)
p = figure(x_axis_type="datetime",
tools="",
title="热度",
x_axis_label='日期',
y_axis_label='天数',
width=400,
height=400)
p.line(s.index, s.values, legend="距离当前天数", line_width=2)
script, div = components(p, CDN)
return [script, div]
else:
return [0, file_hepler.get_image_path("no_hot.png")]
def make_overview_plot(data, p_id):
"""
评价概览
:param datas:
:return:
"""
if data:
temps = "".join(data)
values = re.findall(r'(\d+)', temps)
c_values = [int(value) for value in values]
c_keys = re.findall('[\u4e00-\u9fa5]+', temps)
s = pd.Series(c_values, index=c_keys)
s.plot.bar(figsize=(6, 8), fontsize=8)
plt.savefig("static/upload/%s_o.png" % p_id, dpi=90)
plt.close()
return file_hepler.get_image_path("%s_o.png" % p_id)
else:
return file_hepler.get_image_path("no_overview.png")
def make_comment_plot(data, p_id):
"""
生成好评率的饼图
:param datas:
:return:
"""
if data:
temps = "".join(data).replace(" ", "").replace("\r\n", "")
values = re.findall(r'(\d+)', temps)
c_values = [int(value) for value in values]
c_keys = re.findall('[\u4e00-\u9fa5]+', temps)
print(c_keys)
s = pd.Series(c_values, index=c_keys, name='好评率')
s = s[3:6]
s_sum = s.sum()
s = s.apply(lambda x: x / s_sum)
s.plot.pie(autopct='%0.2f%%', fontsize=8, colors=['g', 'y', 'r'])
plt.savefig("static/upload/%s_c.png" % p_id, dpi=90)
plt.close()
return file_hepler.get_image_path("%s_c.png" % p_id)
else:
return file_hepler.get_image_path("no_good_comments.png")
def make_overview_bokeh(data):
if data:
temps = "".join(data)
values = re.findall(r'(\d+)', temps)
c_values = [int(value) for value in values]
c_keys = re.findall('[\u4e00-\u9fa5]+', temps)
s = pd.Series(c_values, index=c_keys)
data = s
# 创建一个新的含有标题和轴标签的窗口在线窗口
p = Bar(data,
title="总览图",
ylabel='关键字数量',
width=400,
height=400,
legend=None,
tools="")
script, div = components(p, CDN)
return [script, div]
else:
return [0, file_hepler.get_image_path("no_overview.png")]
def make_commment_bokeh(data):
if data:
temps = "".join(data).replace(" ", "").replace("\r\n", "")
values = re.findall(r'(\d+)', temps)
c_values = [int(value) for value in values]
c_keys = re.findall('[\u4e00-\u9fa5]+', temps) #
s = pd.Series(c_values, index=c_keys, name='好评率')
s = s[3:6]
s_sum = s.sum()
s = s.apply(lambda x: x / s_sum * 100)
factors = list(s.index)
x = s.values
dot = figure(title="好评率(单位:%)",
tools=TOOLS,
toolbar_location=None,
y_range=factors,
x_range=[0, 100],
width=400,
height=400)
dot.segment(
0,
factors,
x,
factors,
line_width=2,
line_color="green",
)
dot.circle(
x,
factors,
size=15,
fill_color="orange",
line_color="green",
line_width=3,
)
script, div = components(dot, CDN)
return [script, div]
else:
return [0, file_hepler.get_image_path("no_good_comments.png")]