mpl = LazyImport("import matplotlib as mpl") plt = LazyImport("import matplotlib.pyplot as plt") sns = LazyImport("import seaborn as sns") py = LazyImport("import plotly as py") go = LazyImport("import plotly.graph_objs as go") px = LazyImport("import plotly.express as px") dash...
import numpy.random as npr # numpy是用来做科学计算的 import numpy as np import matplotlib.pyplot as plt # matplotlib是用来画图的 import matplotlib as mpl from collections import Counter # ? import seaborn as sns # ? # import missingno as msno # 用来应对缺失的数据 # Set plotting style # ...
验证seaborn库是否成功安装并可以导入: 安装完成后,你可以通过Python解释器来验证seaborn库是否成功安装。在命令行中输入python或python3启动Python解释器,然后输入以下代码: python import seaborn as sns print(sns.__version__) 如果输出显示了seaborn的版本号,说明seaborn已经成功安装并且可以正常导入。 如果仍然出现...
pyforest中导入的包遵循python社区默认的简称，如pandas>pd、seaborn>sns、matplotlib.pyplot>plt等等。如果...
import pandas as pd import seaborn as sns from sklearn.neural_network import MLPClassifier from sklearn.neighbors import KNeighborsClassifier from sklearn.svm import SVC from sklearn.gaussian_process import GaussianProcessClassifier from sklearn.gaussian_process.kernels import RBF ...
Seaborn 是在Matplotlib 的基础上进行了更高级的API封装的Python数据可视化库,从而使得作图更加容易,应该把 Seaborn 视为Matplotlib 的补充,而不是替代物。 import seaborn as sns import matplotlib.pyplot as plt sns.set_theme(style="ticks") df = sns.load_dataset("penguins") sns.pairplot(df, hue="species...
from sklearn.cluster import KMeans from scipy.sparse import issparse from scipy.stats import binom_test, ks_2samp import matplotlib.pyplot as plt from tqdm.auto import tqdm import random import pandas as pd import numpy as np from numpy.random import choice import seaborn as sns import shap ...
import pandas as pd # In[3]: import matplotlib.pyplot as plt # In[4]: import seaborn as sns # In[5]: get_ipython().run_line_magic('matplotlib', 'inline') # # PreProcessing # In[7]: UNSW = pd.read_csv('/Radhe/Projeto/The UNSW-NB15 data set description/UNSW_NB15_training-set...
import matplotlib.pyplot as plt import seaborn as sns from sklearn.cluster import KMeans from sklearn.cluster import DBSCAN n_samples=1000 X,y=datasets.make_circles(n_samples=n_samples, factor=.5,noise=.05) dbscan=DBSCAN(eps=0.08)
import xlwings as xw import seaborn as sns plt.rc('font',family='Times New Roman') a = 'C:/Users/46685/Desktop/测试/2022年09月医疗指标情况1.xls' b = pd.read_excel(a,sheet_name = 'Exc2475') c=b.dropna(how='all') d=c.loc[c['科室'].str.contains('消化内科|胃肠外科|肝胆胰外...