title: PYTHON: How to get seaborn attributes to reset to default?
body: <p>I cannot for the life of me get seaborn to go back to default settings.
  I will place the code that I believe caused this issue, <strong>but I would recommend against running it</strong> unless you know how to fix it.
  The culprit I believe is in the last chunk
  sns.set(font_scale = 4)
  before this question gets deleted because it's already been asked, I have tried the other posted solutions  with no success. Just to name a quick few, resetting using sns.set(), sns.set_style(), sns.restore_defaults(). I have also tried resetting matplot settings to defaults as well. This attribute persists across all my files, so I cant even open a new file, delete the line of code that caused it, or run any past programs, or it will apply to those graphs too.
  My seaborn version is 0.10.1, I have tried to update it, but I cant get it to go through. I am using anaconda's spyder IDE
  The documentation says for versions after 0.8 that the styles/themes must be invoked to be reset, but if I try to use their solution sns.set_theme() I get an error saying that this module has no attribute.
  I'm sure this persistence is considered a feature, but I desperately need it to go away!</p>
  <pre class="lang-py prettyprint-override"><code>import requests
  import pandas as pd
  import matplotlib.pyplot as plt
  import seaborn as sns
  import os
  if __name__ == '__main__':
      
      #data prep
      data_path = './assets/'
      out_path = './output'
      #scraping javascript map data via xml
      endpoint = &quot;https://covid.cdc.gov/covid-data-tracker/COVIDData/getAjaxData&quot;
      data = requests.get(endpoint, params={&quot;id&quot;: &quot;US_MAP_DATA&quot;}).json()
      #convert to df and export raw data as csv
      df = pd.DataFrame(data[&quot;US_MAP_DATA&quot;])
      path = os.path.join(out_path,'Raw_CDC_Data.csv')
      df.to_csv(path)
      
      #Remove last data point (Total USA)
      df.drop(df.tail(1).index,inplace=True)
      #Create DF of just 50 states
      state_abbr =[&quot;AL&quot;, &quot;AK&quot;, &quot;AZ&quot;, &quot;AR&quot;, &quot;CA&quot;, &quot;CO&quot;, &quot;CT&quot;, &quot;DC&quot;, &quot;DE&quot;, &quot;FL&quot;, &quot;GA&quot;, 
            &quot;HI&quot;, &quot;ID&quot;, &quot;IL&quot;, &quot;IN&quot;, &quot;IA&quot;, &quot;KS&quot;, &quot;KY&quot;, &quot;LA&quot;, &quot;ME&quot;, &quot;MD&quot;, 
            &quot;MA&quot;, &quot;MI&quot;, &quot;MN&quot;, &quot;MS&quot;, &quot;MO&quot;, &quot;MT&quot;, &quot;NE&quot;, &quot;NV&quot;, &quot;NH&quot;, &quot;NJ&quot;, 
            &quot;NM&quot;, &quot;NY&quot;, &quot;NC&quot;, &quot;ND&quot;, &quot;OH&quot;, &quot;OK&quot;, &quot;OR&quot;, &quot;PA&quot;, &quot;RI&quot;, &quot;SC&quot;, 
            &quot;SD&quot;, &quot;TN&quot;, &quot;TX&quot;, &quot;UT&quot;, &quot;VT&quot;, &quot;VA&quot;, &quot;WA&quot;, &quot;WV&quot;, &quot;WI&quot;, &quot;WY&quot;]
      
      
      states = df[df['abbr'].isin(state_abbr)]
      #Adding NYC to state of NY
          # FILL THIS IN LATER
      #Graphing
      plt.style.use('default')
      sns.set()
      #add new col survival rate and save
      states['survival_rate']=states['tot_cases']-states['tot_death']
      states.drop(df.columns[[0]],axis=1)
      states.reset_index(drop=True)
      path = os.path.join(out_path,'CDC_Data_By_State.csv')
      states.to_csv(path)
      #Stacked BarPlot
      fig, ax = plt.subplots()
      colors = ['#e5c5b5','#a8dda8']
      r=range(0,len(states.index))
      plt.bar(r,states['survival_rate'],color=colors[0])
      
      #ax = stacked['survival_rate','tot_death'].plot.bar(stacked=True, color=colors, ax=ax)
      
      fig, ax = plt.subplots()
      plt.figure(figsize=(20,35))
      sns.set(font_scale=4)
      ax = sns.barplot(x='tot_cases',y='abbr',data=states)
      ax.set(title='USA Covid-19 Cases by State', ylabel='State', xlabel='Confirmed Cases')
      path = os.path.join(out_path,'Total_Deaths_Bar.png')
      plt.savefig(path)
  </code></pre>