def pie_count_gender(self):
"""
用户性别分布
:return:
"""
# 分组
gender_df = self.df.groupby(['gender'])['level'].agg(['count'])
gender_df.reset_index(inplace=True)
attr = gender_df['gender']
v = gender_df['count']
pie = Pie('用户性别分布')
pie.add('', attr, v, is_label_show=True, legend_orient="vertical", legend_pos="80%")
return pie
def score_rose_render(score):
from pyecharts import Pie
attr = list(set(score))
value = []
for x in attr:
value.append(score.count(x))
Pie("评分玫瑰饼图分布", title_pos='center').add(
"",
attr,
value,
is_label_show=True,
is_legend_show=False,
radius=[40, 75],
# rosetype="radius",
rosetype="area").render("score_rose.html")
def drawPie(name, rank, chatroomname):
outputFile = './result/{}_群性别比例图.html'.format(chatroomname)
pie = Pie('{} 群性别比例图'.format(chatroomname),
width=1200,
height=600,
title_pos='center')
pie.add(
'',
name,
rank,
is_label_show=True, # 是否显示标签
label_text_color=None, # 标签颜色
legend_orient='vertical', # 图例是否垂直
legend_pos='left')
pie.render(outputFile)
def nk_to_pie(complaints):
data = {}
for i in complaints:
if i.nk[:4].isdigit():
nk = i.nk[:4]
if nk in data.keys():
data[nk] += 1
else:
data[nk] = 1
else:pass
attr = list(data.keys())
value = list(data.values())
pie = Pie('投诉年款分布图', width=1300)
pie.add('', attr, value, is_label_show=True)
return pie
def show_male(dict_data):
'''饼图展示男女比例'''
sex_key_list = []
sex_value_list = []
# 提取数据
for sex_key, sex_value in dict_data.items():
sex_key_list.append(sex_key)
sex_value_list.append(sex_value)
# 创建饼图 title_pos:标题位置
pie = Pie('男女比例', width=1400)
# 添加数据 is_random:是否随机排列颜色，默认false
pie.add("", sex_key_list, sex_value_list, is_label_show=True)
pie.render('./img/男女比例.html')
def showPie(self, title, attr, value):
from pyecharts import Pie
pie = Pie(title)
# pie.add("aa", attr, value, is_label_show=True, title_pos='center')
pie.add(
"",
attr,
value,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
pie.render()
def bw_to_pie(complaints):
data = {}
for i in complaints:
for i in i.wt.split(','):
wt = i.split('#')
if wt[0] in data.keys():
data[wt[0]] += 1
else:
data[wt[0]] = 1
attr = list(data.keys())
value = list(data.values())
pie = Pie('投诉部位分布图',width=1300)
pie.add('',attr,value,is_legend_show=False, is_label_show=True)
return pie
def bingzhuangtu(dict_data, title_info):
'''饼状图'''
list_key = []
list_values = []
for key, values in dict_data.items():
list_key.append(key)
list_values.append(values)
# 创建饼图 title_pos:标题位置
pie = Pie(title_info, width=900)
# 添加数据 is_random:是否随机排列颜色，默认false
pie.add("", list_key, list_values, is_label_show=True)
# pie.show_config()
pie.render('./img/' + title_info + '.html')
def PaintPie(name, school, num):
pie = Pie("山东软件大赛一等奖获奖学校统计-饼图", title_pos='center', width=900)
pie.add(
"山软一等奖获奖学校",
school,
num,
center=[50, 50],
is_random=True,
radius=[30, 75],
rosetype="area",
is_legend_show=False,
is_label_show=True,
)
pie.render(name)
def DrawPie(title, data, savepath='./results'):
if not os.path.exists(savepath):
os.mkdir(savepath)
pie = Pie(title, title_pos='center')
attrs = [i for i, j in data.items()]
values = [j for i, j in data.items()]
pie.add('',
attrs,
values,
is_label_show=True,
radius=[30, 50],
rosetype="radius",
legend_pos="left",
legend_orient="vertical")
pie.render(os.path.join(savepath, '%s.html' % title))
def size_price(size,price):
#page=Page()
overlap=Overlap()
#print(size)
k=[]
attr=['0-30','30-60','60-90','90-120','120-150','150及以上']
for i in range(len(size)):
size[i]=float(size[i][:-2])
n1,n2,n3,n4,n5,n6=[],[],[],[],[],[]
for i in range(len(size)):
if size[i]<=30:
#print(size[i])
n1.append(price[i])
#n1.append(size[i])
if 30<size[i]<=60:
n2.append(price[i])
#n2.append(size[i])
if 60< size[i] <= 90:
n3.append(price[i])
# n3.append(size[i])
if 90<size[i]<=120:
n4.append(price[i])
#n4.append(size[i])
if 120<size[i]<=150:
n5.append(price[i])
#n5.append(size[i])
if 150<size[i]:
n6.append(price[i])
#n6.append(size[i])
l=[len(n1),len(n2),len(n3),len(n4),len(n5),len(n6)]
ave=[numpy.mean(n1),numpy.mean(n2),numpy.mean(n3),numpy.mean(n4),numpy.mean(n5),numpy.mean(n6)]
bar = Bar("房屋面积_数量价位分布图", "", title_pos="left", width=1200, height=600)
bar.add("", attr,ave, is_visualmap=True, visual_text_color='#fff',
is_more_utils=True, is_label_show=True, is_datazoom_show=True, xaxis_rotate=45)
overlap.add(bar)
#page.add(bar)
#bar.render('房屋面积_数量bar.html')
line = Line('房屋面积_均价图', width=1200, height=600)
line.add('数量', attr,l, is_stack=True, mark_point=['max', 'min'],line_color='lightblue',
is_more_utils=True, visual_range=[0, 50])
#page.add(line)
overlap.add(line,is_add_yaxis=True,yaxis_index=1)
#line.render('房屋面积_均价折线图.html')
overlap.render('房屋面积_数量_均价折线图.html')
pie=Pie('面积占比', title_pos='center', width=1200, height=600)
pie.add("", attr, l, label_text_color=None, is_label_show=True, legend_orient='vertical',
is_more_utils=True, legend_pos='left')
pie.render('面积占比Pie.html')
def test_page():
page = Page()
line = Line("折线图示例")
line.chart_id = "id_my_cell_line"
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
)
# pie
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图-圆环图示例", title_pos="center", width="600px")
pie.add(
"",
CLOTHES,
v1,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
page.add([line, pie, create_a_bar(TITLE)])
# Start render and test
html = page._repr_html_()
# Test base html structure
assert html.count("<script>") == html.count("</script>") == 2
assert html.count("<div") == html.count("</div>") == 3
assert html.count("require.config") == html.count("function(echarts)") == 1
# Test some chart attributes
json_encoded_title = json.dumps(TITLE)
assert json_encoded_title in html
assert "nbextensions/echarts" in html # default jshost
assert html.count("height:400px") == 3
assert html.count("width:600px") == 1
assert html.count("width:800px") == 2
assert html.count("id_my_cell_line") == 6
def pic(data, file):
all_poet = [i[0] for i in data]
all_num = [i[1] for i in data]
pie = Pie(title=file.rstrip('2.txt') + '中的四季', title_pos='center')
pie.add(
"",
all_poet,
all_num,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
pie.render(path=file.rstrip('2.txt') + '中的四季' + '.html')
def ePie(myList):
key = []
value = []
for item in myList:
key.append(item[0])
value.append(item[1])
pie = Pie("")
pie.add("热词",
key,
value,
is_label_show=True,
is_legend_show=True,
label_text_color=None,
legend_orient='vertical',
legend_pos='left')
return pie
def user_count_pie(self):
"""
用户地区分布
:return:
"""
# 分组
user_count_df = self.df.groupby(['address'])['level'].agg(['count'])
overseas = user_count_df['count']['海外']
nil = user_count_df['count']['无']
home = user_count_df['count'].sum() - overseas - nil
attr = ['国内', '海外', '无']
value = [home, overseas, nil]
pie = Pie('用户地区分布')
pie.add("", attr, value, is_label_show=True)
return pie
def pie(spi, name):
"""
:param spi: 接受为元组((),())
:param name:
:return:
"""
attr = []
v1 = []
for i in spi:
attr.append(i[0])
v1.append(i[1])
pie_pie = Pie(name, title_pos='center')
pie_pie.add("", attr, v1, radius=[40, 75], label_text_color=None,
is_label_show=True, legend_orient='vertical', legend_pos='left')
return pie_pie.render_embed()
def mCityAll(dfAll, minit):
df_ = dfAll.drop('id', axis=1).groupby('city').agg([len])
attr = list(df_.index)
value = list(df_['count']['len'])
pie = Pie("")
pie.add(
"各个城市的油站数量",
attr,
value,
is_random=True,
rosetype="area",
is_legend_show=False,
is_label_show=True,
legend_pos="20%",
)
pie.render('img-各个城市的油站数量.html')
def stars_of_bread(data):
stars = data['Star'].value_counts().sort_index()
stars_pcc = data.groupby('Star')['Per_Consumption'].mean()
starts_fig = Pie("Stars of Restaurant", title_pos='center')
starts_fig.add('', ['0星', '2星', '3星', '3.5星', '4星', '4.5星', '5星'],
stars.values,
legend_pos='left',
legend_orient='vertical',
is_label_show=True,
rosetype='radius')
starts_fig.render(os.path.join(data_out, 'stars_of_bread.html'))
plt.figure()
# plt.axis(rotation=90)
stars_pcc.plot(kind='barh')
plt.show()
def drawPie(value):
#画出不同时区的店铺的分布数量饼状图
dict1 = Counter(value)
# print(dict1.keys())
attr = dict1.keys()
v = dict1.values()
pie = Pie("饼图示例", "正代表东，负代表西，数字代表第几个时区,30代表这条记录缺失时区值", title_pos='center')
pie.add("",
attr,
v,
center=[50, 60],
is_label_show=True,
label_text_color=None,
legend_orient='vertical',
legend_pos='left')
pie.render("timezone_pie.html")
def build_top10_dst_port_diagram(df, logs):
df_top10_grouped_by_dst_port = None
if not df.empty:
df_top10_grouped_by_dst_port = df.groupby('dstport').agg({'msg': 'count'})\
.sort_values(by='msg').tail(10)
attr = list(df_top10_grouped_by_dst_port.index
) if df_top10_grouped_by_dst_port is not None else {}
v = list(df_top10_grouped_by_dst_port['msg']
) if df_top10_grouped_by_dst_port is not None else {}
pie = Pie()
pie.add("DST Port", attr, v)
logs.update(top10_dst_port_diagram=pie.render_embed())
logs.update(echart_pie_script_list=pie.get_js_dependencies())
def create_profession(data, title):
page = Page()
style = Style(width=900,
height=400,
title_pos="center",
background_color='#c4ccd3')
kwargs = dict(radius=(40, 75),
label_text_color=None,
is_label_show=True,
legend_orient='her',
legend_pos='left')
profession_chart = Pie(title, **style.init_style)
attr, value = profession_chart.cast(data)
profession_chart.add("", attr, value, **kwargs)
page.add(profession_chart)
return page
def ReadOther():
attr = ["城市社区服务", "环保项目", "帮扶活动", "文体活动", "安全医疗", "法律宣传讲座培训", "其他"]
value = [373257, 159648, 212721, 246070, 143465, 120205, 93256]
funnel = Funnel("项目类别统计", width='100%', height='100%', title_pos='center',
title_text_size=16, title_color='#3B5077')
funnel.add("类别统计", attr, value, is_label_show=True, label_pos="inside", label_text_color="#fff",
label_text_size=8, legend_orient="vertical", legend_pos="left", legend_text_size=10)
name = []
value = []
with open('data/全国院校统计前100.csv', 'r', encoding='utf-8') as file:
reader = csv.reader(file)
for row in reader:
name.append(row[2])
value.append(row[1])
wordcloud = WordCloud(width='120%', height='100%')
wordcloud.add("", name, value, word_size_range=[8, 30])
schema = [
("博士研究生", 1000000), ("硕士研究生", 1000000), ("大学本科", 1000000), ("大学专科", 1000000), ("中等专科", 1000000),
("技工学校", 1000000), ("高中", 1000000), ("初中", 1000000), ("职业高中", 1000000), ("小学", 1000000),
]
v1 = [[9979, 48300, 716519, 448358, 118656, 36065, 600168, 697599, 54160, 270191]]
v2 = [[863336, 462984, 953627, 646927, 234893, 170111, 354992, 241914, 158316, 84504]]
radar = Radar(width='100%', height='110%')
radar.config(schema)
radar.add("实际人数分布", v1, is_splitline=True, is_axisline_show=True, label_text_size=8, legend_orient="vertical")
radar.add("人数比例分布", v2, label_color=["#4e79a7"], is_area_show=False,
legend_selectedmode='single', legend_pos="right", legend_text_size=10, legend_orient="vertical")
attr = ["群众", "中国少年先锋队队员", "无党派民主人士", "台湾民主自治同盟盟员", "九三学社社员", "中国致公党党员", "中国农工民主党党员",
"中国民主促进会会员", "中国民主建国会会员", "中国民主同盟盟员", "中国国民党革命委员会会员", "中国共产主义青年团团员", "中国共产党预备党员", "中国共产党党员"]
v2 = [34688546, 2725751, 95275, 2180, 713840, 3787, 30049, 7356, 7278, 14952, 21065, 12621879, 294148, 6089445]
pie = Pie(width='100%', height='90%', title_pos='center', title_text_size=10)
pie.add("政治面貌统计", attr, v2, center=[50, 50], is_random=True, radius=[10, 80], rosetype="area",
is_legend_show=True, is_label_show=False, legend_pos="left", legend_text_size=10, legend_orient="vertical")
attr = ['2005', '2006', '2007', '2008', '2009', '2010', '2011',
'2012', '2013', '2014', '2015', '2016', '2017', '2018']
line = Line(width='100%', height='100%')
line.add("志愿者数增长", attr, [1, 59580, 532707, 258196, 26194, 628465, 311171, 1970707, 1539836,
2807952, 6566130, 6775399, 36504414, 7408478], mark_line=["average"])
line.add("团体增长", attr, [371, 485, 471, 924, 798, 1266, 2887, 4963, 4848, 7781, 24203, 15936, 25280, 5376],
mark_line=["average"])
line.add("项目增长", attr, [10, 6, 3, 94, 125, 152, 210, 802, 3209, 10937, 58426, 166609, 341083, 203931],
mark_line=["average"], legend_text_size=10, yaxis_label_textsize=8, yaxis_margin=2)
return funnel, wordcloud, radar, pie, line
def GuanJianCi(self, data_name="None", num=20, text=None):
page = Page()
if text == None:
text = "SimHash是一种局部敏感hash，它也是Google公司进行海量网页去重使用的主要算法。传统的Hash算法只负责将原始内容尽量均匀随机地映射为一个签名值，原理上仅相当于伪随机数产生算法。传统的hash算法产生的两个签名，如果原始内容在一定概率下是相等的；如果不相等，除了说明原始内容不相等外，不再提供任何信息，因为即使原始内容只相差一个字节，所产生的签名也很可能差别很大。所以传统的Hash是无法在签名的维度上来衡量原内容的相似度，而SimHash本身属于一种局部敏感哈希算法，它产生的hash签名在一定程度上可以表征原内容的相似度。我们主要解决的是文本相似度计算，要比较的是两个文章是否相似，当然我们降维生成了hash签名也用于这个目的。看到这里估计大家就明白了，我们使用的simhash就算把文章中的字符串变成 01 串也还是可以用于计算相似度的，而传统的hash却不行。"
tags = jieba.analyse.extract_tags(text,
topK=num,
withWeight=True,
withFlag=True)
name = []
value = []
for tag in tags:
name.append(tag[0])
value.append(tag[1])
print(value)
wordCloud = WordCloud(data_name)
wordCloud.add("", name, value)
pie = Pie('前十个词汇占重', "", title_pos='center')
style = Style()
pie_style = style.add(label_pos="center",
is_label_show=True,
label_text_color=None)
hight = 10
width = 30
sum_Wight = sum(value)
for index, (n, v) in enumerate(zip(name, value)):
if index == 5:
hight = 10
width = width + 40
if index < 10:
pie.add("", [n, ""], [v / sum_Wight, 1 - v / sum_Wight],
center=[hight, width],
radius=[18, 24],
**pie_style)
hight = hight + 20
print(hight, width)
print index
page.add(pie)
page.add(wordCloud)
save_helper.save_tu_helper(page, data_name)
def make_pie():
drugs = []
stocks = []
res = mysql_conn.exec_readsql("select drug_name,stock from drug_info")
for i in res:
drugs.append(i[0])
stocks.append(i[1])
print drugs
#pie = Pie("药品库存显示",title_pos='center',width=900)
pie = Pie("药品库存显示 药品销量显示", title_pos='center', width=1000)
pie.add("",
drugs,
stocks,
center=[25, 50],
is_random=True,
radius=[30, 75],
legend_orient="vertical",
legend_pos="left")
#pie.add("药品销量情况",drugs,stocks,center=[25,50],is_random=True,radius=[30,75],rosetype='radius')
drugs = []
sells = []
res_2 = mysql_conn.exec_readsql("select drug_name,sum(drug_amount)\
from transaction_list,drug_info where transaction_list.drug_id=drug_info.drug_id\
group by transaction_list.drug_id")
for i in res_2:
drugs.append(str(i[0].encode('utf-8')))
sells.append(str(i[1]))
for i in drugs:
print i
pie.add("药品销量情况",
drugs,
sells,
center=[65, 50],
is_random=True,
radius=[30, 75],
legend_orient="vertical",
legend_pos="right")
pie.render('./templates/render_drug.html')
def PaintRosePie(school, number, name):
pie = Pie(name, title_pos='center', width=900)
pie.add(
"获奖情况",
school,
number,
center=[50, 50],
is_random=True,
radius=[30, 75],
rosetype="area",
is_legend_show=True,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
pie.render(name + '.html')
def showPie(self):
title = ' 公司类型'
attr, value = self.get_company_type()
pie = Pie(title)
# pie.add("aa", attr, value, is_label_show=True, title_pos='center')
pie.add(
"",
attr,
value,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
pie.render('公司类型.html')
def test_grid_line_pie():
line = Line("折线图示例", width=1200)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="55%")
pie.add("", attr, v1, radius=[45, 65], center=[65, 50], legend_pos="80%",
legend_orient='vertical')
grid = Grid()
grid.add(line, grid_right="55%")
grid.add(pie, grid_left="60%")
grid.render()
def draw_pie_mulit():
attr = ['A', 'B', 'C', 'D', 'E', 'F']
pie = Pie("饼图示例", width=1000, height=600)
pie.add("",
attr, [random.randint(0, 100) for _ in range(6)],
radius=[50, 55],
center=[25, 50],
is_random=True)
pie.add("",
attr, [random.randint(20, 100) for _ in range(6)],
radius=[0, 45],
center=[25, 50],
rosetype='area')
#pie.add("", attr, [random.randint(0, 100) for _ in range(6)], radius=[50, 55], center=[65, 50],is_random=True)
#pie.add("", attr, [random.randint(20, 100) for _ in range(6)], radius=[0, 45], center=[65, 50],rosetype='radius')
pie.show_config()
pie.render()
def showHotPie(keys=getHotWords()):
content = getAllContents()
labels, values = myCal(content, keys)
pie = Pie("水利热点比例图", title_pos='center')
#pie.add("",labels,values,is_label_show=True)
pie.add(
"",
labels,
values,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
# pie.render()
return pie
def pie_chart(w=600,
h=400,
is_show=True,
is_toolbox_show=True,
is_legend_show=True):
chart = Charts.query.filter_by(name='pie').first()
current_chart_paras = chart.inf.all()
pie = Pie(chart.tit,
"",
title_pos='center',
width=w,
height=h,
title_color='#fff',
title_text_size=12)
attr = []
v = []
info = Msg.query.filter()
for i in current_chart_paras:
v.append(i.info_value)
attr.append(i.info_name)
# 获取JSON数据
with open('map.json', 'r') as f:
data = json.load(f)
num_blue = data["blue"]
num_red = data["red"]
label_color = ['#bbd3b1', "#8db978", '#669f40', '#548534']
# v = [num_red, num_blue]
pie.add('',
attr,
v,
legend_pos='right',
legend_orient='vertical',
rosetype='radius',
radius=[40, 70],
legend_text_color='#fff',
label_color=label_color,
is_label_show=is_show,
is_toolbox_show=is_toolbox_show,
is_legend_show=is_legend_show)
return pie