def t3(pa):
hm = p.HeatMap('地区职位与需求关系', width=1500, height=600)
hm.add("需求量",
next(pa),
next(pa),
next(pa),
is_visualmap=True,
visual_range=[350, 25000],
visual_text_color="#000",
visual_orient='horizontal',
yaxis_label_textsize=8,
yaxis_rotate=-45,
is_toolbox_show=False)
return hm
def confusion_matrix_map(y_true,
y_pred,
jupyter=True,
path="Confusion Matrix Map.html"):
t = confusion_matrix(y_true, y_pred)
t = pd.DataFrame([[i, m, n] for i, j in t.to_dict().items()
for m, n in j.items()],
columns=['actual', 'predict', 'over_values'])
heatmap = pe.HeatMap("Confusion Matrix Map")
heatmap.add("Confusion Matrix",
t.drop_duplicates(['actual']).actual.values,
t.drop_duplicates(['predict']).predict.values,
t.values,
is_visualmap=True,
xaxis_name='Actual',
yaxis_name='Predict',
visual_text_color="#000",
visual_orient="horizontal",
visual_range=[0, t.over_values.max()])
return heatmap if jupyter else heatmap.render(path)
def creat_Heatmap():
x_axis = [
"12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a",
"11a", "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",
"10p", "11p"
]
y_aixs = [
"Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday",
"Sunday"
]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = pyecharts.HeatMap()
heatmap.add("热力图直角坐标系",
x_axis,
y_aixs,
data,
is_visualmap=True,
visual_text_color="#000",
visual_orient='horizontal')
# heatmap.render('Heatmap-weather.html')
page.add(heatmap)
top_kw_percentage_df[i] = pd.Series(list(kw['percentage']),
index=kw['kw'])
top_kw_percentage_df.fillna(0, inplace=True)
top_kw_percentage_df.to_csv('top_kw_percentage_df.csv')
data = []
i = 0
for index in top_kw_percentage_df.index:
j = 0
for score in top_kw_percentage_df.columns:
data.append([j, i, top_kw_percentage_df[score][index] * 100])
j += 1
i += 1
# 创建热力图展示结果
heatmap = pec.HeatMap()
heatmap.add("",
top_kw_percentage_df.columns,
top_kw_percentage_df.index,
data,
is_visualmap=True,
visual_text_color='#000',
visual_range=[0, 10],
visual_orient='horizontal')
heatmap.render(path='top_heatmap.html')
# 创建柱状图展示结果
bar3d = pec.Bar3D("3D 柱状图示例", width=1200, height=600)
range_color = [
'#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'
"12a", "1a", "2a", "3a", "4a", "5a", "6a",
"7a", "8a", "9a", "10a", "11a", "12p", "1p",
"2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",
"10p", "11p",
]
y_axis = [
"Saturday",
"Friday",
"Thursday",
"Wednesday",
"Tuesday",
"Monday",
"Sunday",
]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = echarts.HeatMap("热力图示例")
heatmap.add(
"热力图直角坐标系",
x_axis,
y_axis,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient="horizontal",
)
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = echarts.Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)