def echart04(request):
template = loader.get_template('ewpyecharts.html')
cursor = connection.cursor()
query_sql = "select typen, count(*) f1, sum(order_m) as f2, sum(status) f3, max(order_m) f4, avg(order_m) f5 from myechart_ewsales group by typen"
cursor.execute(query_sql)
data = cursor.fetchall()
# query_sql = "select name, f1, f2 from swap_radas order by f2 desc limit 0,5"
# data = exc_sql(query_sql)
data = list(data)
data = [list(i) for i in data]
# df = DataFrame(data, columns=["name", "f1", "f2"])
df = DataFrame(data, columns=["typen", "f1", "f2", "f3", "f4", "f5"])
df[["f1", "f2", "f3", "f4", "f5"]] = df[["f1", "f2", "f3", "f4",
"f5"]].astype(float)
df = df.sort_values(by='f1', ascending=False)
# f1 数量, f2 金额, f2 成功率, f4 最大金额, F5 平均金额
df1 = df['typen']
df2 = df[['f1', 'f2', 'f3', 'f4', 'f5']]
# 用于调整雷达各维度的范围大小
c_schema = [{
"name": "数量",
"max": df['f1'].max(),
"min": -1
}, {
"name": "金额",
"max": df['f2'].max(),
"min": -1
}, {
"name": "成功率",
"max": df['f3'].max(),
"min": -1
}, {
"name": "最大金额",
"max": df['f4'].max(),
"min": -1
}, {
"name": "平均金额",
"max": df['f5'].max(),
"min": -1
}]
#
# 画图
d1 = [[0.79, 0.90, 0.46, 0.57, -0.50]]
# d3 = df2[:1].values.tolist()
radar = Radar()
radar.config(c_schema=c_schema)
# radar.add(df1[1], df2[:1].values.tolist())
# radar.add(df1[2], df2[:2].values.tolist())
# radar.add(df1[3], df2[:3].values.tolist())
# radar.add(df1[4], df2[:4].values.tolist())
# radar.add(df1[5], df2[:5].values.tolist())
radar.add(df1[0:1].values, df2[0:1].values.tolist())
radar.add(df1[1:2], df2[1:2].values.tolist())
radar.add(df1[2:3], df2[2:3].values.tolist())
radar.add(df1[3:4], df2[3:4].values.tolist())
radar.add(df1[4:5], df2[4:5].values.tolist())
# radar.add("数量", [d1])
# radar.add("金额", [d2])
# radar.add("数量", [d1])
context = dict(myechart=radar.render_embed(),
host=REMOTE_HOST,
script_list=radar.get_js_dependencies())
return HttpResponse(template.render(context, request))
def echart03(request):
template = loader.get_template('ewpyecharts.html')
# 2个系列的5个维度的数据
# value1 = [[0.79, 0.90, 0.46, 0.57, -0.50]]
# value2 = [[0.11, 0.34, 0.31, -0.11, 0.21]]
d1 = [[0.79, 0.90, 0.46, 0.57, -0.50]]
d2 = [[1.11, 0.34, 0.31, -0.11, 0.21]]
# sqldata_m = []
# query_sql = "select count(*) 数量, sum(order_m) as 金额, sum(status) 成功率, max(order_m) 最大金额, avg(order_m) 平均金额, typen from myechart_ewsales"
# data_list = exc_sql(query_sql)
# m=[i[0] for i in data_list]
#
# query_sql = "select max(f1), max(f2) from swap_radas "
# data_list = exc_sql(query_sql)
# m1 = data_list[0]
# m2 = data_list[1]
query_sql = "select name, f1, f2 from swap_radas order by f2 desc limit 0,5"
data = exc_sql(query_sql)
data = list(data)
data = [list(i) for i in data]
df = DataFrame(data, columns=["name", "f1", "f2"])
n = list(df["name"])
d1 = list(df["f1"])
d2 = list(df["f2"])
# dd1 = [float(i[1]) for i in data_list]
# d1 = list(dd1)
# d2 = [i[2] for i in data_list]
# query_sql = "select count(*) 数量, sum(order_m) as 金额, sum(status) 成功率, max(order_m) 最大金额, avg(order_m) 平均金额, typen from myechart_ewsales where typen = '营销体系'"
# data_list = exc_sql(query_sql)
# d2 = [i[0] for i in data_list]
#
# # 用于调整雷达各维度的范围大小
# c_schema = [{"name": "", "max": 1, "min": -1},
# {"name": "", "max": 1, "min": -1},
# {"name": "", "max": 1, "min": -1},
# {"name": "", "max": 1, "min": -1},
# {"name": "", "max": 1, "min": -1}]
# 用于调整雷达各维度的范围大小
c_schema = [{
"name": n[0],
"max": 1,
"min": -1
}, {
"name": n[1],
"max": 1,
"min": -1
}, {
"name": n[2],
"max": 1,
"min": -1
}, {
"name": n[3],
"max": 1,
"min": -1
}, {
"name": n[4],
"max": 1,
"min": -1
}]
# 画图
radar = Radar()
radar.config(c_schema=c_schema)
radar.add("数量", [d1])
radar.add("金额", [d2])
context = dict(myechart=radar.render_embed(),
host=REMOTE_HOST,
script_list=radar.get_js_dependencies())
return HttpResponse(template.render(context, request))
def echart1(request):
template = loader.get_template('ewpyecharts.html')
sql_s = "select typen, count(*) f1, sum(order_m) as f2, sum(status) f3, max(order_m) f4, avg(order_m) f5 from myechart_ewsales group by typen"
columns_s = ["typen", "f1", "f2", "f3", "f4", "f5"]
# index_col_s = "f1"
df = pd.read_sql(sql_s, connection, columns=columns_s)
df = df.sort_values(by='f1', ascending=False)
# f1 数量, f2 金额, f2 成功率, f4 最大金额, F5 平均金额
# old_width = pd.get_option('display.max_colwidth')
# pd.set_option('display.max_colwidth', -1)
# df.to_html('files.html', escape=False, index=False, sparsify=True, border=0, index_names=False, header=False)
# pd.set_option('display.max_colwidth', old_width
df1 = list(df['typen'])
df2 = df[['f1', 'f2', 'f3', 'f4', 'f5']]
# 用于调整雷达各维度的范围大小
c_schema = [{
"name": "数量201910",
"max": df['f1'].max(),
"min": -1
}, {
"name": "金额2019",
"max": df['f2'].max(),
"min": -1
}, {
"name": "成功率",
"max": df['f3'].max(),
"min": -1
}, {
"name": "最大金额",
"max": df['f4'].max(),
"min": -1
}, {
"name": "平均金额",
"max": df['f5'].max(),
"min": -1
}]
#
# 画图
radar = Radar()
radar.config(c_schema=c_schema)
radar.add(df1[0],
df2[0:1].values.tolist(),
item_color="#f9713c",
symbol=None,
area_color="#ea3a2e",
area_opacity=0.1,
legend_top='bottom',
line_width=3)
radar.add(df1[1],
df2[1:2].values.tolist(),
item_color='#2525f5',
symbol=None,
area_color='#2525f5',
area_opacity=0.1,
legend_top='bottom',
legend_text_size=20,
line_width=3)
radar.add(df1[2],
df2[2:3].values.tolist(),
item_color='#112535',
line_width=3)
radar.add(df1[3],
df2[3:4].values.tolist(),
item_color='#991125',
line_width=3)
radar.add(df1[4],
df2[4:5].values.tolist(),
item_color='#1125b9',
line_width=3)
radar.render("Rader.html")
context = dict(myechart=radar.render_embed(),
host=REMOTE_HOST,
script_list=radar.get_js_dependencies())
html_out = template.render(context, request)
# attr = ["衬衫", "羊毛衫", "始祖鸟", "裤子", "高跟鞋", "袜子"]
# v1 = [5, 20, 36, 10, 75, 90]
# v2 = [10, 25, 8, 60, 20, 80]
# bar1 = Bar("柱状图数据堆叠示例")
# bar1.add("商家A", attr, v1, is_stack=True)
# bar1.add("商家B", attr, v2, is_stack=True)
#
# context = dict(
# bar=bar1.render_embed(),
# host=REMOTE_HOST,
# script_list=bar.get_js_dependencies()
# )
# return HttpResponse(template.render(context, request))
return HttpResponse(html_out)
