我正在尝试为客户状态迁移制作一个有向图或Sankey图(任何可行的方法)。数据如下所示,计数表示从当前状态迁移到下一个状态的用户数量。
**current_state next_state count**
New Profile Initiated 37715
Profile Initiated End 36411
JobRecommended End 6202
New End 6171
ProfileCreated JobRecommended 5799
Profile Initiated ProfileCreated 4360
New NotOpted 3751
NotOpted Profile Initiated 2817
JobRecommended InterestedInJob 2542
IntentDetected ProfileCreated 2334
ProfileCreated IntentDetected 1839
InterestedInJob Applied 1671
JobRecommended NotInterestedInJob 1477
NotInterestedInJob ProfileCreated 1408
IntentDetected End 1325
NotOpted End 1009
InterestedInJob ProfileCreated 975
Applied IntentDetected 912
NotInterestedInJob IntentDetected 720
Applied ProfileCreated 701
InterestedInJob End 673
我已经编写了构建sankey的代码,但是该图不容易阅读。寻找可读的有向图。这是我的代码:
df = pd.read_csv('input.csv')
x = list(set(df.current_state.values) | set(df.next_state))
di = dict()
count = 0
for i in x:
di[i] = count
count += 1
#
df['source'] = df['current_state'].apply(lambda y : di[y])
df['target'] = df['next_state'].apply(lambda y : di[y])
#
fig = go.Figure(data=[go.Sankey(
node = dict(
pad = 15,
thickness = 20,
line = dict(color = "black", width = 0.5),
label = x,
color = "blue"
),
link = dict(
source = df.source,
target = df.target,
value = df['count']
))])
#
fig.update_layout(title_text="Sankey Diagram", font_size=10, autosize=False,
width=1000,
height=1000,
margin=go.layout.Margin(
l=50,
r=50,
b=100,
t=100,
pad=4
))
fig.show()
最佳答案
对于有向图,graphviz
将是我选择的工具,而不是Python。
以下脚本txt2dot.py
将您的数据转换为graphviz的输入文件:
text = '''New Profile Initiated 37715
Profile Initiated End 36411
JobRecommended End 6202
New End 6171
ProfileCreated JobRecommended 5799
Profile Initiated ProfileCreated 4360
New NotOpted 3751
NotOpted Profile Initiated 2817
JobRecommended InterestedInJob 2542
IntentDetected ProfileCreated 2334
ProfileCreated IntentDetected 1839
InterestedInJob Applied 1671
JobRecommended NotInterestedInJob 1477
NotInterestedInJob ProfileCreated 1408
IntentDetected End 1325
NotOpted End 1009
InterestedInJob ProfileCreated 975
Applied IntentDetected 912
NotInterestedInJob IntentDetected 720
Applied ProfileCreated 701
InterestedInJob End 673'''
# Remove ambiguity and make suitable for graphviz.
text = text.replace('New Profile', 'NewProfile')
text = text.replace('New ', 'NewProfile ')
text = text.replace('Profile Initiated', 'ProfileInitiated')
text = text.replace(' Initiated', ' ProfileInitiated')
# Create edges and nodes for graphviz.
edges = [ln.split() for ln in text.splitlines()]
edges = sorted(edges, key=lambda x: -1*int(x[2]))
nodes = sorted(list(set(i[0] for i in edges) | set(i[1] for i in edges)))
print('digraph foo {')
for n in nodes:
print(f' {n};')
print()
for item in edges:
print(' ', item[0], ' -> ', item[1], ' [label="', item[2], '"];', sep='')
print('}')
运行
python3 txt2dot.py > foo.dot
会导致:digraph foo {
Applied;
End;
IntentDetected;
InterestedInJob;
JobRecommended;
NewProfile;
NotInterestedInJob;
NotOpted;
ProfileCreated;
ProfileInitiated;
NewProfile -> ProfileInitiated [label="37715"];
ProfileInitiated -> End [label="36411"];
JobRecommended -> End [label="6202"];
NewProfile -> End [label="6171"];
ProfileCreated -> JobRecommended [label="5799"];
ProfileInitiated -> ProfileCreated [label="4360"];
NewProfile -> NotOpted [label="3751"];
NotOpted -> ProfileInitiated [label="2817"];
JobRecommended -> InterestedInJob [label="2542"];
IntentDetected -> ProfileCreated [label="2334"];
ProfileCreated -> IntentDetected [label="1839"];
InterestedInJob -> Applied [label="1671"];
JobRecommended -> NotInterestedInJob [label="1477"];
NotInterestedInJob -> ProfileCreated [label="1408"];
IntentDetected -> End [label="1325"];
NotOpted -> End [label="1009"];
InterestedInJob -> ProfileCreated [label="975"];
Applied -> IntentDetected [label="912"];
NotInterestedInJob -> IntentDetected [label="720"];
Applied -> ProfileCreated [label="701"];
InterestedInJob -> End [label="673"];
}
运行
dot -o foo.png -Tpng foo.dot
可提供:关于python - 在Python中绘制有向图?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/59484773/