英文:
Initial plot not clearing when using dropdown menu to choose new data
问题
我正在自学如何使用ipywidgets包，通过对每个国家的总covid死亡人数进行分析，并希望创建一个带有下拉菜单的交互式图表来选择国家。
我的代码几乎完美运行。唯一的问题是，当我选择一个新的国家时，初始图表不会清除，我会留下两个图表，选择的正确图表和初始图表（如下图所示）。
请问有人能指导我如何去除初始图表吗？
以下是我正在使用的代码：
import numpy as npimport pandas as pdimport matplotlib.pyplot as pltimport ipywidgets as widgetsimport seaborn as sns# 获取数据集data_url = "https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/cases_deaths/total_deaths_per_million.csv"df = pd.read_csv(data_url, index_col=0, parse_dates=[0], engine='python')# 将缺失值填充为0df.fillna(0, inplace=True)df.head()# 添加年周列df['Year_Week'] = df.index.to_period('W').strftime('%Y-%U')# 仅保留每周最后一天并更改为日期时间类型df = df.groupby(df['Year_Week']).last('1D')df.index = pd.to_datetime(df.index + '-0', format='%Y-%U-%w')# 删除不是国家的列df_country = df.drop(['World','Africa','Asia','Europe','European Union','High income','Low income','Lower middle income','North America','South America','Upper middle income'],axis=1)# 创建函数以根据所选国家更新图表def update_plot(country):ax.clear() # 清除现有图表ax.plot(df.index, df_country[country]) # 绘制所选国家# 设置x轴刻度位置和标签xticks = pd.date_range(start=df_country.index[0].strftime('%Y-01-01'), end=df_country.index[-1], freq='AS')xticklabels = [x.strftime('%Y') for x in xticks]ax.set_xticks(xticks)ax.set_xticklabels(xticklabels)ax.set_title(f"每百万人的总死亡人数 ({country})") # 更新图表标题ax.set_xlabel("日期")ax.set_ylabel("每百万人的死亡人数")fig.canvas.draw() # 重新绘制画布# 创建包含国家名称作为选项的下拉菜单country_dropdown = widgets.Dropdown(options=df_country.columns,value=df_country.columns[0],description='国家')# 创建图表fig, ax = plt.subplots()update_plot(country_dropdown.value) # 初始图表# 设置小部件交互output = widgets.Output()display(country_dropdown, output)def on_change(change):if change['type'] == 'change' and change['name'] == 'value':with output:output.clear_output()update_plot(change['new'])display(fig)country_dropdown.observe(on_change)
英文:
I am teaching myself how to use the ipywidgets package by doing analysis on the total covid deaths for each country and want to make an interactive plot with a dropdown menu for Country choice.
My code works almost perfectly. The only thing is that when I chose a new country, the initial plot does not clear and I am left with 2 plots, the correct plot from choice, and the initial plot (as seen in the image below).
Can someone please point me in the right direction as to how I can remove the initial plot?
Here is the code that I am using:
import numpy as npimport pandas as pdimport matplotlib.pyplot as pltimport ipywidgets as widgetsimport seaborn as sns# Get datasetdata_url = "https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/cases_deaths/total_deaths_per_million.csv"df = pd.read_csv(data_url, index_col=0, parse_dates=[0], engine='python')# na values = 0df.fillna(0, inplace=True)df.head()# add year-week columndf['Year_Week'] = df.index.to_period('W').strftime('%Y-%U')# keep only last day of week and change to datetime typedf = df.groupby(df['Year_Week']).last('1D')df.index = pd.to_datetime(df.index + '-0', format='%Y-%U-%w')# drop columns that aren't a countrydf_country = df.drop(['World','Africa','Asia','Europe','European Union','High income','Low income','Lower middle income','North America','South America','Upper middle income'],axis=1)# create function to update plot based on selected countrydef update_plot(country):ax.clear() # clear existing plotax.plot(df.index, df_country[country]) # plot selected country# set x-axis tick locations and labelsxticks = pd.date_range(start=df_country.index[0].strftime('%Y-01-01'), end=df_country.index[-1], freq='AS')xticklabels = [x.strftime('%Y') for x in xticks]ax.set_xticks(xticks)ax.set_xticklabels(xticklabels)ax.set_title(f"Total deaths per million ({country})") # update plot titleax.set_xlabel("Date")ax.set_ylabel("Deaths per million")fig.canvas.draw() # redraw canvas# create drop-down menu with country names as optionscountry_dropdown = widgets.Dropdown(options=df_country.columns,value=df_country.columns[0],description='Country')# create plotfig, ax = plt.subplots()update_plot(country_dropdown.value) # initial plot# set up widget interactionoutput = widgets.Output()display(country_dropdown, output)def on_change(change):if change['type'] == 'change' and change['name'] == 'value':with output:output.clear_output()update_plot(change['new'])display(fig)country_dropdown.observe(on_change)
答案1
得分: 1
If you're working in a notebook, make your plot interactive by adding %matplotlib widget at the beginning of the cell.
Then, you don't need to use Output, simply update your fig and re-draw it in the event callback function.
%matplotlib widget# [...]# create plotfig, ax = plt.subplots()update_plot(country_dropdown.value) # initial plot# set up widget interactiondisplay(country_dropdown)def on_change(change):if change['type'] == 'change' and change['name'] == 'value':update_plot(change['new'])plt.draw()country_dropdown.observe(on_change)
Execute the cell
Change the dropdown value. The figure is updated in the cell output without the initial one
英文:
If you're working in a notebook, make your plot interactive by adding %matplotlib widget at the beginning of the cell.
Then, you don't need to use Output, simply update your fig and re-draw it in the event callback function.
%matplotlib widget# [...]# create plotfig, ax = plt.subplots()update_plot(country_dropdown.value) # initial plot# set up widget interactiondisplay(country_dropdown)def on_change(change):if change['type'] == 'change' and change['name'] == 'value':update_plot(change['new'])plt.draw()country_dropdown.observe(on_change)
Execute the cell
Change the dropdown value. The figure is updated in the cell output without the initial one
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