I have this Dataframe: OverallQual Foundation 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 BrkTil 8 PConc 8 PConc 8 CBlock 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 BrkTil 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 Wood 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 CBlock 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 8 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 CBlock 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 9 PConc 10 BrkTil 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 PConc 10 BrkTil 10 PConc 10 PConc 10 CBlock 10 PConc And if I count the values of each Foundation in every OverallQual, it show the result like this: OverallQual Foundation 8 BrkTil 2 CBlock 10 PConc 155 Wood 1 9 CBlock 1 PConc 42 10 BrkTil 2 CBlock 1 PConc 15 Name: count, dtype: int64 I want to produce a faceted grid of bar plots, one for each OverallQual and then colour the bars according to the Foundation column. I try to use FacetGrid in this case. Here's my code df_exerc_fg = sns.FacetGrid(df_exerc, col='OverallQual', hue='Foundation',palette='tab10') df_exerc_fg.map(sns.barplot, 'Foundation', 'OverallQual') But the result is not like what I expected. I think it's not plotting correctly. But when I compared this with subplot in this code: fig,ax = plt.subplots(1, 3, sharey=True, sharex=True, figsize=(15,5)) plt.suptitle(str.title('Material pondasi yang sering dipakai untuk grade 8-10'), fontsize=16) ax[0].set_title('Overall = 8', fontsize=14) sns.barplot(x = train_house['Foundation'].loc[train_house.OverallQual == 8].value_counts().index, y = train_house['Foundation'].loc[train_house.OverallQual == 8].value_counts(), hue = train_house['Foundation'].loc[train_house.OverallQual == 8].value_counts().index, legend=False, palette='tab10', ax=ax[0]) ax[1].set_title('Overall = 9', fontsize=14) sns.barplot(x = train_house['Foundation'].loc[train_house.OverallQual == 9].value_counts().index, y = train_house['Foundation'].loc[train_house.OverallQual == 9].value_counts(), hue = train_house['Foundation'].loc[train_house.OverallQual == 9].value_counts().index, legend=False, palette='tab10', ax=ax[1]) ax[2].set_title('Overall = 10', fontsize=14) sns.barplot(x = train_house['Foundation'].loc[train_house.OverallQual == 10].value_counts().index, y = train_house['Foundation'].loc[train_house.OverallQual == 10].value_counts(), hue = train_house['Foundation'].loc[train_house.OverallQual == 10].value_counts().index, legend=False, palette='tab10', ax=ax[2]) plt.show() It plot the data perfectly, like this. The chart in FacetGrid is not plotting correctly. What am I missing in my code? Continue reading...
