flask vs django(vs fastAPI) flask 튜토리얼 flask vs django https://ddi-dev.com/blog/programming/django-vs-flask-which-better-your-web-app/ https://morioh.com/p/a91d4f7a5eb2 https://www.youtube.com/watch?v=gvzEcCF_yv8&ab_channel=GKTechFlex https://wendys.tistory.com/172 단순 REST API 서버 구축 flask가 효율적 flask 튜토리얼 https://www.tutorialspoint.com/flask/index.htm 0. Home - flask: web application framework(Py..
아마 거의 모든 데이터 셋에는 missing value가 존재 missing value 처리 방법은 간단히 두가지 지운다. : deletion 채운다. : imputation imputation 방법은 크게 두가지 simple multivariate simple imputation If “mean”, then replace missing values using the mean along each column. Can only be used with numeric data. If “median”, then replace missing values using the median along each column. Can only be used with numeric data. If “most_frequent”..
reference: https://matplotlib.org/3.1.0/gallery/color/named_colors.html List of named colors — Matplotlib 3.1.0 documentation Note Click here to download the full example code List of named colors This plots a list of the named colors supported in matplotlib. Note that xkcd colors are supported as well, but are not listed here for brevity. For more information on colors in matplo matplotlib.org
1. shap version check and building a explainer 2. matplotlib colormap, make color dictionary 3. shap.summary_plot 1. shap version check and building a explainer 사용한 shap version : 0.37.0 import shap shap.initjs() print(shap.__version__) building a explainer # changing names of features names = pd.read_csv('~/name_dictionary.csv', index_col='var') background = shap.maskers.Independent(X_train_fea..
#1. kdeplot #2. get x, y #3. get max or min #4. marking import seaborn as sns import numpy as np #1. ax = sns.kdeplot(th_box_sub2, label='sub2') #2. x = ax.lines[0].get_xdata() # Get the x data of the distribution y = ax.lines[0].get_ydata() # Get the y data of the distribution #3. maxid1 = np.argmax(y) # get max in all maxid2 = np.argmax(y[x0.56) & (x0.56) & (x0.56) & (x0.56) & (x
