我正在尝试绘制三个图表(日、月、年)，并让用户可以通过下拉菜单选择他们想要查看的图表。当我为(日，月)执行此操作时，它工作得很好(月份显示为默认图表)，但是当我添加(年)时，(日，月)不显示(在这种情况下，我想要年作为默认图表)。
这是工作代码:
# Plot Day
temp_day = pd.DataFrame(df.day.value_counts())
temp_day.reset_index(inplace=True)
temp_day.columns = ['day', 'tweet_count']
temp_day.sort_values(by=['day'], inplace=True)
temp_day.reset_index(inplace=True, drop=True)
trace_day = go.Scatter(
x=temp_day.day.values,
y=temp_day.tweet_count.values,
text = [f"{humanize.naturaldate(day)}: {count} tweets" for day,count in zip(temp_day.day.values,temp_day.tweet_count.values)],
hoverinfo='text',
mode='lines',
line = {
'color': my_color,
'width': 1.2
},
visible=False,
name="Day"
)
# Plot Month
temp_month = pd.DataFrame(df.YYYYMM.value_counts())
temp_month.reset_index(inplace=True)
temp_month.columns = ['YYYYMM', 'tweet_count']
temp_month['YYYYMM'] = temp_month['YYYYMM'].dt.strftime('%Y-%m')
temp_month.sort_values(by=['YYYYMM'], inplace=True)
temp_month.reset_index(inplace=True, drop=True)
trace_month = go.Scatter(
x=temp_month.YYYYMM.values,
y=temp_month.tweet_count.values,
mode='lines',
line = {
'color': my_color,
'width': 1.2
},
visible=True,
name="Month"
)
# Menus
updatemenus = list([
dict(
active=0,
buttons=list([
dict(label = 'Month',
method = 'update',
args = [{'visible': [True, False]},
{'title': 'Number of Tweets per Month'}]),
dict(label = 'Day',
method = 'update',
args = [{'visible': [False, True]},
{'title': 'Number of Tweets per Day'}]),
]),
)
])
# Layout
layout = go.Layout(title="Number of Tweets -- Pick a scale",
updatemenus=updatemenus,
)
fig = go.Figure(data=[trace_month, trace_day], layout=layout)
iplot(fig)这是不起作用的代码，我不知道为什么:
# Plot Day
temp_day = pd.DataFrame(df.day.value_counts())
temp_day.reset_index(inplace=True)
temp_day.columns = ['day', 'tweet_count']
temp_day.sort_values(by=['day'], inplace=True)
temp_day.reset_index(inplace=True, drop=True)
trace_day = go.Scatter(
x=temp_day.day.values,
y=temp_day.tweet_count.values,
text = [f"{humanize.naturaldate(day)}: {count} tweets" for day,count in zip(temp_day.day.values,temp_day.tweet_count.values)],
hoverinfo='text',
mode='lines',
line = {
'color': my_color,
'width': 1.2
},
visible=False,
name="Day"
)
# Plot Month
temp_month = pd.DataFrame(df.YYYYMM.value_counts())
temp_month.reset_index(inplace=True)
temp_month.columns = ['YYYYMM', 'tweet_count']
temp_month['YYYYMM'] = temp_month['YYYYMM'].dt.strftime('%Y-%m')
temp_month.sort_values(by=['YYYYMM'], inplace=True)
temp_month.reset_index(inplace=True, drop=True)
trace_month = go.Scatter(
x=temp_month.YYYYMM.values,
y=temp_month.tweet_count.values,
mode='lines',
line = {
'color': my_color,
'width': 1.2
},
visible=False,
name="Month"
)
# Plot year
temp_year = pd.DataFrame(df.year.value_counts())
temp_year.reset_index(inplace=True)
temp_year.columns = ['year', 'tweet_count']
temp_year.sort_values(by=['year'], inplace=True)
temp_year.reset_index(inplace=True, drop=True)
trace_year = go.Scatter(
x=temp_year.year.values,
y=temp_year.tweet_count.values,
text = [f"Year {year}: {count:,.0f} tweets" for year,count in zip(temp_year.year.values,temp_year.tweet_count.values)],
hoverinfo='text',
mode='lines+markers',
line = {
'color': my_color,
'width': 1.2
},
visible=True,
name="Year"
)
# Menus
updatemenus = list([
dict(
active=0,
buttons=list([
dict(label = 'Year',
method = 'update',
args = [{'visible': [True, False, False]},
{'title': 'Number of Tweets per Month'}]),
dict(label = 'Month',
method = 'update',
args = [{'visible': [False, True, False]},
{'title': 'Number of Tweets per Month'}]),
dict(label = 'Day',
method = 'update',
args = [{'visible': [False, False, True]},
{'title': 'Number of Tweets per Day'}]),
]),
)
])
# Layout
layout = go.Layout(title="Number of Tweets -- Pick a scale",
updatemenus=updatemenus,
)
fig = go.Figure(data=[trace_year, trace_month, trace_day], layout=layout)
iplot(fig)这是数据:
# Year
Scatter({
'hoverinfo': 'text',
'line': {'color': '#ff00a7', 'width': 1.2},
'mode': 'lines+markers',
'name': 'Year',
'text': [Year 2011: 73 tweets, Year 2012: 562 tweets, Year 2013: 1,153 tweets,
Year 2014: 700 tweets, Year 2015: 2,104 tweets, Year 2016: 1,816
tweets, Year 2017: 1,691 tweets, Year 2018: 1,082 tweets, Year 2019:
914 tweets, Year 2020: 482 tweets],
'visible': False,
'x': array([2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020]),
'y': array([ 73, 562, 1153, 700, 2104, 1816, 1691, 1082, 914, 482])
})
# Month
Scatter({
'line': {'color': '#ff00a7', 'width': 1.2},
'mode': 'lines',
'name': 'Month',
'visible': False,
'x': array(['2011-06', '2011-07', '2011-08', '2011-09', '2011-10', '2011-11',
'2011-12', '2012-01', '2012-02', '2012-03', '2012-04', '2012-05',
'2012-06', '2012-07', '2012-08', '2012-09', '2012-10', '2012-11',
'2012-12', '2013-01', '2013-02', '2013-03', '2013-04', '2013-05',
'2013-06', '2013-07', '2013-08', '2013-09', '2013-10', '2013-11',
'2013-12', '2014-01', '2014-02', '2014-03', '2014-04', '2014-05',
'2014-06', '2014-07', '2014-08', '2014-09', '2014-10', '2014-11',
'2014-12', '2015-01', '2015-02', '2015-03', '2015-04', '2015-05',
'2015-06', '2015-07', '2015-08', '2015-09', '2015-10', '2015-11',
'2015-12', '2016-01', '2016-02', '2016-03', '2016-04', '2016-05',
'2016-06', '2016-07', '2016-08', '2016-09', '2016-10', '2016-11',
'2016-12', '2017-01', '2017-02', '2017-03', '2017-04', '2017-05',
'2017-06', '2017-07', '2017-08', '2017-09', '2017-10', '2017-11',
'2017-12', '2018-01', '2018-02', '2018-03', '2018-04', '2018-05',
'2018-06', '2018-07', '2018-08', '2018-09', '2018-10', '2018-11',
'2018-12', '2019-01', '2019-02', '2019-03', '2019-04', '2019-05',
'2019-06', '2019-08', '2019-09', '2019-10', '2019-11', '2019-12',
'2020-01', '2020-02', '2020-03', '2020-04', '2020-05', '2020-06'],
dtype=object),
'y': array([ 1, 1, 2, 8, 4, 20, 37, 79, 16, 13, 8, 12, 2, 5,
68, 139, 57, 64, 99, 182, 63, 60, 74, 128, 59, 109, 126, 86,
77, 112, 77, 78, 44, 32, 22, 33, 46, 61, 66, 109, 81, 78,
50, 140, 151, 297, 173, 225, 69, 119, 213, 177, 134, 217, 189, 255,
149, 114, 127, 154, 116, 110, 150, 184, 179, 117, 161, 48, 115, 147,
153, 199, 174, 195, 154, 162, 114, 140, 90, 156, 81, 107, 62, 64,
49, 128, 127, 60, 89, 115, 44, 58, 86, 65, 102, 93, 82, 78,
158, 65, 50, 77, 55, 71, 70, 105, 124, 57])
})
# Day
Scatter({
'hoverinfo': 'text',
'line': {'color': '#ff00a7', 'width': 1.2},
'mode': 'lines',
'name': 'Day',
'text': [Jun 04 2011: 1 tweets, Jul 17 2011: 1 tweets, Aug 11 2011: 1 tweets,
..., Jun 17: 4 tweets, Jun 18: 1 tweets, Jun 19: 3 tweets],
'visible': False,
'x': array([datetime.date(2011, 6, 4), datetime.date(2011, 7, 17),
datetime.date(2011, 8, 11), ..., datetime.date(2020, 6, 17),
datetime.date(2020, 6, 18), datetime.date(2020, 6, 19)], dtype=object),
'y': array([1, 1, 1, ..., 4, 1, 3])
})最佳答案
由于您提供了一个不起作用的数据样本，因此很难分辨代码片段中哪些有效，哪些无效。但是，我确实有一个建议可以直接回答您的问题:
I am trying to plot three graphs (day, month, year) and give the user the option to pick which graph they want to see with a dropdown menu
下面的代码片段将让您在两个数据集之间进行选择:
year和 month .这些是您提供的确切数据集。当您获得 days 的工作样本时，该数据集可以很容易地包含在内。当你准备好时，我很乐意为你做这件事。不管怎样，下面的 plotly 会让你选择
year和 month使用下拉菜单。如果设计 wrt 线条和标记样式不符合您的喜好，请不要担心。这只是作为占位符包含在代码中，供您根据需要进行更改。年
月
天
(待定……)
完整代码
import plotly.graph_objects as go
import pandas as pd
df_y=pd.DataFrame({'x':[2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020],
'y':[ 73, 562, 1153, 700, 2104, 1816, 1691, 1082, 914, 482]})
df_m=pd.DataFrame({'x':['2011-06', '2011-07', '2011-08', '2011-09', '2011-10', '2011-11',
'2011-12', '2012-01', '2012-02', '2012-03', '2012-04', '2012-05',
'2012-06', '2012-07', '2012-08', '2012-09', '2012-10', '2012-11',
'2012-12', '2013-01', '2013-02', '2013-03', '2013-04', '2013-05',
'2013-06', '2013-07', '2013-08', '2013-09', '2013-10', '2013-11',
'2013-12', '2014-01', '2014-02', '2014-03', '2014-04', '2014-05',
'2014-06', '2014-07', '2014-08', '2014-09', '2014-10', '2014-11',
'2014-12', '2015-01', '2015-02', '2015-03', '2015-04', '2015-05',
'2015-06', '2015-07', '2015-08', '2015-09', '2015-10', '2015-11',
'2015-12', '2016-01', '2016-02', '2016-03', '2016-04', '2016-05',
'2016-06', '2016-07', '2016-08', '2016-09', '2016-10', '2016-11',
'2016-12', '2017-01', '2017-02', '2017-03', '2017-04', '2017-05',
'2017-06', '2017-07', '2017-08', '2017-09', '2017-10', '2017-11',
'2017-12', '2018-01', '2018-02', '2018-03', '2018-04', '2018-05',
'2018-06', '2018-07', '2018-08', '2018-09', '2018-10', '2018-11',
'2018-12', '2019-01', '2019-02', '2019-03', '2019-04', '2019-05',
'2019-06', '2019-08', '2019-09', '2019-10', '2019-11', '2019-12',
'2020-01', '2020-02', '2020-03', '2020-04', '2020-05', '2020-06'],
'y':[ 1, 1, 2, 8, 4, 20, 37, 79, 16, 13, 8, 12, 2, 5,
68, 139, 57, 64, 99, 182, 63, 60, 74, 128, 59, 109, 126, 86,
77, 112, 77, 78, 44, 32, 22, 33, 46, 61, 66, 109, 81, 78,
50, 140, 151, 297, 173, 225, 69, 119, 213, 177, 134, 217, 189, 255,
149, 114, 127, 154, 116, 110, 150, 184, 179, 117, 161, 48, 115, 147,
153, 199, 174, 195, 154, 162, 114, 140, 90, 156, 81, 107, 62, 64,
49, 128, 127, 60, 89, 115, 44, 58, 86, 65, 102, 93, 82, 78,
158, 65, 50, 77, 55, 71, 70, 105, 124, 57]})
# IMPROVEMENT 1
# INSERT ANOTHER DATAFRAME FOR DAYS HERE WITH THE SAME STRUCTURE AS ABOVE
# IMPROVEMENT 1
# INCLUDE THE DATAFRAME AS VALUE AND THE NAME df_d as key
# in the dict below:
dfc = {'year':df_y, 'month':df_m}
# set index
for df in dfc.keys():
dfc[df].set_index('x', inplace=True)
# plotly start
fig = go.Figure()
# menu setup
updatemenu= []
# buttons for menu 1, names
buttons=[]
# plotly start
fig = go.Figure()
# one trace for each column per dataframe: AI and RANDOM
for df in dfc.keys():
fig.add_trace(go.Scatter(x=dfc[df].index,
y=dfc[df]['y'],
visible=True,
#marker=dict(size=12, line=dict(width=2)),
#marker_symbol = 'diamond',
name=df
)
)
# some line settings for fun
lines = [dict(color='royalblue', width=2, dash='dot'), dict(color='firebrick', width=1, dash='dash')]
markers = [dict(size=12, line=dict(width=2)), dict(size=12, line=dict(width=2))]
# create traces for each color:
# build argVals for buttons and create buttons
for i, df in enumerate(dfc.keys()):
args_y = []
args_x = []
for col in dfc[df]:
args_y.append(dfc[df][col].values)
args_x.append(dfc[df].index)
argVals = [ {'y':args_y, 'x':args_x,
'marker':markers[i], 'line': lines[i]}]
buttons.append(dict(method='update',
label=df,
visible=True,
args=argVals))
updatemenu=[]
your_menu=dict()
updatemenu.append(your_menu)
updatemenu[0]['buttons']=buttons
updatemenu[0]['direction']='down'
updatemenu[0]['showactive']=True
fig.update_layout(showlegend=False, updatemenus=updatemenu)
fig.show()
关于python - Plotly:如何使用下拉菜单按年、月和日对数据进行子集化？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/62501451/