seaborn displot()未在定义的子图中绘制 [英] seaborn displot() is not plotting within defined subplots

问题描述

我正在尝试与此代码并排绘制两个凹痕

  fig，(ax1，ax2)= plt.subplots(1,2)sns.displot(x = X_train ['Age']，hue = y_train，ax = ax1)sns.displot(x = X_train ['Fare']，hue = y_train，ax = ax2) 

它返回以下结果(两个空子图，然后在两行中各显示一个图)-

如果我用violinplot尝试相同的代码，它将返回预期的结果

  fig，(ax1，ax2)= plt.subplots(1,2)sns.violinplot(y_train，X_train ['Age']，ax = ax1)sns.violinplot(y_train，X_train ['Fare']，ax = ax2) 

为什么Displot返回不同类型的输出，我该怎么做才能在同一行上输出两个图?

解决方案

• 摘录自
  • 对于长格式的数据框，请使用 displot

   #创建一个长数据框dfl = pd.DataFrame(penins [['species'，'bill_length_mm'，'bill_depth_mm']].set_index('species').stack()).reset_index().rename(columns = {'level_1':'bill_size'，0:'vals'})#disply(dfl.head())种类bill_size vals0阿德利bill_length_mm 39.11阿德利bill_depth_mm 18.72阿德利bill_length_mm 39.53阿德利bill_depth_mm 17.44阿德利bill_length_mm 40.3# 阴谋sns.displot(data = dfl，x ='vals'，col ='bill_size'，kind ='hist'，kde = True) 

  I am trying to plot two displots side by side with this code

  fig,(ax1,ax2) = plt.subplots(1,2)
  
  sns.displot(x =X_train['Age'], hue=y_train, ax=ax1)
  sns.displot(x =X_train['Fare'], hue=y_train, ax=ax2)
  

  It returns the following result (two empty subplots followed by one displot each on two lines)-

  If I try the same code with violinplot, it returns result as expected

  fig,(ax1,ax2) = plt.subplots(1,2)
  
  sns.violinplot(y_train, X_train['Age'], ax=ax1)
  sns.violinplot(y_train, X_train['Fare'], ax=ax2)
  

  Why is displot returning a different kind of output and what can I do to output two plots on the same line?

  解决方案

  • From the documentation for seaborn.distplot, which has been DEPRECATED in seaborn 0.11.
  • .distplot is replaced with the following:
    • displot(), a figure-level function with a similar flexibility over the kind of plot to draw. This is a FacetGrid, and does not have the ax parameter.
    • histplot(), an axes-level function for plotting histograms, including with kernel density smoothing. This does have the ax parameter.
  • Because the histogram of two different columns is desired, it's easier to use histplot.

  fig,(ax1,ax2) = plt.subplots(1,2)
  
  sns.histplot(x=X_train['Age'], hue=y_train, ax=ax1)
  sns.histplot(x=X_train['Fare'], hue=y_train, ax=ax2)
  

  Example

  • With the data in a wide format, use sns.histplot

  import seaborn as sns
  
  # load data
  penguins = sns.load_dataset("penguins", cache=False)
  
  # display(penguins.head())
    species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  body_mass_g     sex
  0  Adelie  Torgersen            39.1           18.7              181.0       3750.0    MALE
  1  Adelie  Torgersen            39.5           17.4              186.0       3800.0  FEMALE
  2  Adelie  Torgersen            40.3           18.0              195.0       3250.0  FEMALE
  3  Adelie  Torgersen             NaN            NaN                NaN          NaN     NaN
  4  Adelie  Torgersen            36.7           19.3              193.0       3450.0  FEMALE
  
  # set x and y
  x, y = penguins.bill_length_mm, penguins.bill_depth_mm
  
  # plot
  fig, (ax1, ax2) = plt.subplots(1, 2)
  
  sns.histplot(x, kde=True, ax=ax1)
  sns.histplot(y, kde=True, ax=ax2)
  plt.tight_layout()
  

  • With the dataframe in a long format, use displot

  # create a long dataframe
  dfl = pd.DataFrame(penguins[['species', 'bill_length_mm', 'bill_depth_mm']].set_index('species').stack()).reset_index().rename(columns={'level_1': 'bill_size', 0: 'vals'})
  
  # disply(dfl.head())
    species       bill_size  vals
  0  Adelie  bill_length_mm  39.1
  1  Adelie   bill_depth_mm  18.7
  2  Adelie  bill_length_mm  39.5
  3  Adelie   bill_depth_mm  17.4
  4  Adelie  bill_length_mm  40.3
  
  # plot
  sns.displot(data=dfl, x='vals', col='bill_size', kind='hist', kde=True)
  

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