def create_type_likes(df):
# 分组求和
likes_type_message = df.groupby(['category'])
likes_type_com = likes_type_message['likes'].agg(['sum'])
likes_type_com.reset_index(inplace=True)
# 处理数据
dom = []
for name, num in zip(likes_type_com['category'], likes_type_com['sum']):
data = {}
data['name'] = name
data['value'] = num
dom.append(data)
print(dom)
# 初始化配置
treemap = TreeMap(init_opts=opts.InitOpts(width="800px", height="400px"))
# 添加数据
treemap.add('', dom)
# 设置全局配置项，标题、工具箱(下载图片)
treemap.set_global_opts(title_opts=opts.TitleOpts(title="各类型抖音大V点赞数汇总图",
pos_left="center",
pos_top="5"),
toolbox_opts=opts.ToolboxOpts(
is_show=True, feature={"saveAsImage": {}}),
legend_opts=opts.LegendOpts(is_show=False))
treemap.render("各类型抖音大V点赞数汇总图.html")
def make_star_treemap(self):
"""
根据演员参演电影数生成矩形树图
:return:
"""
# print(get_current_time() + '|-------> 正在生成 演员参演电影数 图表...')
# 导入数据并初始化
csv_path = os.path.abspath(os.path.join(os.path.dirname("__file__"), os.path.pardir, "moviespider", "movie_info_top500.csv"))
rows = pd.read_csv(csv_path, encoding='utf-8', dtype=str)
# rows = pd.read_csv('../comments/movie_info_top500.csv', encoding='utf-8', dtype=str)
to_drop = ['名称', '导演', '年份', '国别', '类型', '语言', '评分', '评分人数', '五星占比', '四星占比', '三星占比', '二星占比', '一星占比', '短评数',
'简介']
res = rows.drop(to_drop, axis=1)
# 数据分割
all_star_list = []
for i in res.itertuples():
# print(i[1] + '\n')
for j in i[1].split(','):
all_star_list.append(j)
# 数据统计
df = pd.DataFrame(all_star_list, columns=['演员'])
res = df.groupby('演员')['演员'].count().sort_values(ascending=False)
all_star_list = []
for i in res.items():
if i[1] > 4:
all_star_list.append({"value": i[1], "name": i[0]})
# 生成图标
c = TreeMap()
c.add("参演电影数", all_star_list)
c.set_global_opts(title_opts=opts.TitleOpts(title="电影TOP500榜单中 - 演员参演电影数", subtitle="至少参演5部影评以上"))
htmlPath = os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), "analyse_data", "演员参演电影数.html"))
pngPath = os.path.abspath(os.path.join(os.path.abspath(os.path.dirname(os.path.dirname(__file__))), "analyse_data", "演员参演电影数.png"))
# 生成html
c.render(htmlPath)
# 生成png
# make_snapshot(snapshot, c.render(), pngPath)
# print(get_current_time() + '|-------> 已生成 演员参演电影数 图表...')
return c
def create_type_fans(df):
dom = []
fans_type_message = df.groupby(['category'])
fans_type_com = fans_type_message['fans'].agg(['sum'])
fans_type_com.reset_index(inplace=True)
for name, num in zip(fans_type_com['category'], fans_type_com['sum']):
data = {}
data['name'] = name
data['value'] = num
dom.append(data)
print(dom)
treemap = TreeMap(init_opts=opts.InitOpts(width="800px", height="400px"))
treemap.add('', dom)
treemap.set_global_opts(title_opts=opts.TitleOpts(title="各类型抖音大V粉丝数汇总图",
pos_left="center",
pos_top="5"),
toolbox_opts=opts.ToolboxOpts(
is_show=True, feature={"saveAsImage": {}}),
legend_opts=opts.LegendOpts(is_show=False))
treemap.set_series_opts(treemapbreadcrumb_opts=opts.TreeMapBreadcrumbOpts(
is_show=False))
treemap.render("各类型抖音大V粉丝数汇总图.html")
def show_genres():
data=select_data()
# 矩形树图初始化
treemap = TreeMap(init_opts=opts.InitOpts(page_title="豆瓣电影-电影类型分布"))
# 添加数据
treemap.add(
series_name='电影类型',
data=data,
# 标签居中
label_opts=opts.LabelOpts(font_size=15, position="inside"),
)
# 全局配置
treemap.set_global_opts(
# 标题
title_opts=opts.TitleOpts(
title="豆瓣电影-电影类型分布", pos_left='center'
),
# 标签隐藏
legend_opts=opts.LegendOpts(is_show=False)
)
# 生成HTML
html="pages/iframes/genres.html"
treemap.render("./templates/"+html)
return html
def to_treemap(data, proj, version):
complexity = {'name': f'{proj}-{version}', 'children': []}
extract(complexity, 'complexity', data)
maintainability = {'name': f'{proj}-{version}', 'children': []}
extract(maintainability, 'maintainability', data)
testability = {'name': f'{proj}-{version}', 'children': []}
extract(testability, 'testability', data)
readability = {'name': f'{proj}-{version}', 'children': []}
extract(readability, 'readability', data)
reusability = {'name': f'{proj}-{version}', 'children': []}
extract(reusability, 'reusability', data)
inheritance = {'name': f'{proj}-{version}', 'children': []}
extract(inheritance, 'inheritance', data)
treemap = TreeMap()
for indicator in [
'complexity', 'maintainability', 'testability', 'readability',
'reusability', 'inheritance'
]:
treemap = treemap.add(series_name=indicator,
data=[locals()[indicator]],
leaf_depth=2,
roam=False,
label_opts=opts.LabelOpts(position='inside'))
treemap = (treemap.set_global_opts(
tooltip_opts=opts.TooltipOpts(formatter='{b}<br/>{a}: {c}'),
toolbox_opts=opts.ToolboxOpts(feature=opts.ToolBoxFeatureOpts(
magic_type=opts.ToolBoxFeatureMagicTypeOpts(is_show=False),
data_zoom=opts.ToolBoxFeatureDataZoomOpts(is_show=False),
brush=opts.ToolBoxFeatureBrushOpts(type_='clear'))),
legend_opts=opts.LegendOpts(is_show=True,
selected_mode='single',
pos_top='7%',
orient='horizontal',
padding=0),
title_opts=opts.TitleOpts(
title=f'Code Quality Treemap of {proj}-{version}',
pos_left='center')))
grid = Grid()
grid.add(treemap, grid_opts=opts.GridOpts(pos_top='100%'))
return grid
def plot_tree(self, depth=3):
data = self.describe_tree(self.tree)
tree_map = TreeMap()
tree_map.add(self.name, data, leaf_depth=depth, width=800, height=600)
tree_map.render()
return tree_map
def treeMapChart(df):
type_of_plot = st.selectbox("Select Type of Plot",["TreeMap1 Multi-level","TreeMap2"])
# allc = list(df.columns[:20])
# allc
# tmap = px.treemap(df,path=[allc, "Enfants de 0 à 14 ans", "CJE"], values= "Population 2016")
# return tmap
all_columns = df.columns
treemap = TreeMap()
if type_of_plot == "TreeMap1 Multi-level":
columns_to_plot = st.selectbox("Select 1 column",all_columns,key='a' )
columns_to_plot1 = st.selectbox("Select 2 column",[col for col in df.columns if col not in [columns_to_plot]], key='b' )
# columns_to_plot2 = st.selectbox("Select 3 column",[col for col in df.columns if col not in [columns_to_plot, columns_to_plot1]], key='c' )
names = list(df[columns_to_plot])
def get_all_values(d):
if isinstance(d, dict):
for v in d.values():
yield from get_all_values(v)
elif isinstance(d, list):
for v in d:
yield from get_all_values(v)
else:
yield d
dictionaryObject = df.to_dict();
# print(list(get_all_values(dictionaryObject)))
df2 = df.copy()
df3 = df.drop('CJE', axis=1)
df3.values.tolist()
values_market = df3.values.tolist()
df2 = df.copy()
# print(values_market)
childs = []
for j,indu_one in enumerate(names):
data_now = df2[df2[columns_to_plot]==indu_one]
data_1 = list(data_now[columns_to_plot])
# print(data_now.values.tolist())
child = []
child.extend({'name':data_1[i],'value':list(data_now[columns_to_plot])[i]} for i in range(0,len(data_now[columns_to_plot])))
childs.append(child)
data_n = [{ 'name':i,'value':j, 'children': m} for i,j,m in zip(names,values_market,childs)]
treemap.add(series_name="option",data=data_n,visual_min=300,leaf_depth=1,
label_opts=opts.LabelOpts(position="inside"),)
return treemap
if type_of_plot == "TreeMap2":
columns_to_plot = st.selectbox("Select 1 column",all_columns,key='a' )
columns_to_plot1 = st.selectbox("Select 1 column",[col for col in df.columns if col not in [columns_to_plot]], key='b' )
names = list(df[columns_to_plot])
values_market = list(df[columns_to_plot1])
df2 = df.copy()
childs = []
data_n = [{'name':i, 'value':j,'value1':j} for i,j in zip(names,values_market)]
# treemap = TreeMap(init_opts=opts.InitOpts(height='1080px',width='1920px'))
treemap.add(
series_name=columns_to_plot1,
data=data_n,
leaf_depth=2,
node_click="zoomToNode",
zoom_to_node_ratio=0.5*0.5,
levels=[
opts.TreeMapLevelsOpts(
#color_mapping_by='value',
upper_label_opts= opts.LabelOpts(position="inside") ,
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color="#555", border_width=4, gap_width=4
)
),
opts.TreeMapLevelsOpts(
upper_label_opts= opts.LabelOpts(position="inside"),
color_saturation=[0.3, 0.6],
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
border_color_saturation=0.7, gap_width=2, border_width=2
),
),
# opts.TreeMapLevelsOpts(
# color_saturation=[0.3, 0.5],
# treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
# border_color_saturation=0.6, gap_width=1
# ),
# ),
# opts.TreeMapLevelsOpts(color_saturation=[0.3, 0.5]),
],
)
treemap.set_series_opts(label_opts=opts.LabelOpts(
is_show = True,
position = 'inside',# position 'top'，'left'，'right'，'bottom'，'inside'，'insideLeft'，'insideRight'.....
font_size = 20,
# color
color= '#ffffff',
# font_style 'normal'，'italic'，'oblique'
font_style = 'nomal' ,
# font_weight 'normal'，'bold'，'bolder'，'lighter'
font_weight = None,
# font_family 'Arial', 'Courier New', 'Microsoft YaHei' ....
font_family = 'Microsoft YaHei',
# rotate -90 90
rotate = '0',
# margin
margin = 20,
interval = None,
# horizontal_align 'left'，'center'，'right'
horizontal_align = 'center',
# vertical_align ：'top'，'middle'，'bottom'
vertical_align = None,
) )
treemap.set_global_opts(toolbox_opts=opts.ToolboxOpts(pos_left='8%'),
title_opts=opts.TitleOpts(title="TreeMap"))
return treemap
"name":
"我是B",
"children": [{
"value":
76,
"name":
"我是B.children",
"children": [
{
"value": 12,
"name": "我是B.children.a"
},
{
"value": 28,
"name": "我是B.children.b"
},
{
"value": 20,
"name": "我是B.children.c"
},
{
"value": 16,
"name": "我是B.children.d"
},
],
}],
},
]
maptree = TreeMap()
maptree.add("", data).render_notebook()
import json
from pyecharts.charts import TreeMap
import pyecharts.options as opts
with open('GDP_data_1.json', 'r', encoding='utf-8') as f:
j = json.load(f)
data = [j]
map = TreeMap(init_opts=opts.InitOpts(width='1200px', height='800px'))
map.add(
'',
data,
label_opts=opts.LabelOpts(position='inside'),
)
map.render('map.html')
import json
from pyecharts.charts import TreeMap
import pyecharts.options as opts
with open('GDP_data_1.json', 'r', encoding='utf-8') as f:
j = json.load(f)
data = [j]
map = TreeMap(
init_opts=opts.InitOpts(width='1200px', height='800px')
)
map.add('', data, label_opts=opts.LabelOpts(position='inside'), leaf_depth=1)
map.render('map(1).html')
def generate_treemap_html(cur,
title,
key_field_name,
area_field_name,
click_link,
area_data_name='数量',
area_data_unit='个'):
data, item_opts = [], []
min_rise = 100
max_rise = -100
for row in cur.fetchall():
item = get_dict_row(cur, row)
rise_value = item['涨跌']
if rise_value > max_rise:
max_rise = rise_value
if rise_value < min_rise:
min_rise = rise_value
if rise_value > 0:
rise = '\n+{}%'.format(rise_value)
rich = {
'name': {
'fontSize': 14,
'color': '#000'
},
'涨跌': {
'fontSize': 14,
'fontWeight': 'bolder',
"align": "center",
'color': '#FF0000'
}
}
tree_item = opts.TreeMapItemStyleOpts(color_alpha=1,
color='rgb(255,0,0)',
border_color='#fff')
else:
rise = '\n{}%'.format(rise_value)
rich = {
'name': {
'fontSize': 14,
'color': '#000'
},
'涨跌': {
'fontSize': 14,
'fontWeight': 'bolder',
"align": "center",
'color': '#2E8B57'
}
}
tree_item = opts.TreeMapItemStyleOpts(color_alpha=1,
color='rgb(60,179,113)',
border_color='#fff')
data.append(
opts.TreeItem(
name=item[key_field_name],
# value 包含持仓占比和涨跌幅两项数据
value=[item[area_field_name], rise_value],
label_opts=opts.LabelOpts(position='insideBottomLeft',
formatter='{name|{b}}{rise|%s}' %
rise,
rich=rich)))
item_opts.append(tree_item)
color_range, rise_range = calc_range(max_rise, min_rise)
tooltip_js = """function (param)
{ const color = param.value[1] > 0 ? '#FF0000' : '#2E8B57';
const detail_style = `color:${color};`;
const msgContent = `<div style='width:fit-content;height:fit-content;'>
${param.name}<br/>
""" + area_data_name + """： <span style='color:'#fff';'> ${param.value[0]} """ + area_data_unit + """  </span><br/>
涨跌： <span style='${detail_style};'> ${param.value[1]} %  </span><br/>
<div>`;
return msgContent}
"""
tp = TreeMap(init_opts=opts.InitOpts(
theme='white', width='1424px', height='700px', chart_id='cb_tree_map'))
tp.add_js_funcs(
"""
chart_cb_tree_map.on('click', function(params){
// alert(params)
window.location.replace('""" + click_link +
"""?key=' + encodeURIComponent(params['data']['name']) + '&rise=' + params['data']['value'][1] + '#cb_detail_list')
})
""")
tp.add(
'ALL',
data,
roam=False,
node_click='link',
width='90%',
breadcrumb_opts=opts.TreeMapBreadcrumbOpts(is_show=False),
levels=[
opts.TreeMapLevelsOpts(
treemap_itemstyle_opts=opts.TreeMapItemStyleOpts(
gap_width=1, stroke_width=1, stroke_color='#fff'),
color_mapping_by='value',
)
],
tooltip_opts=opts.TooltipOpts(
is_show=True,
formatter=JsCode(tooltip_js),
textstyle_opts=opts.TextStyleOpts(font_size=14)),
color_mapping_by='value',
)
tp.set_global_opts(
title_opts=opts.TitleOpts(title=title,
pos_left='center',
pos_top='30px'),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(
is_show=False,
type_='color',
min_=min_rise,
max_=max_rise,
range_color=color_range,
# 指定使用的数据维度
dimension=1,
is_piecewise=True,
pieces=rise_range),
)
return tp.render_embed('template.html', env)