# Import Data df = pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/mpg_ggplot2.csv") df_select = df.loc[df.cyl.isin([4,8]),:] # Plot sns.set_style("white") gridobj = sns.lmplot(x="displ", y="hwy", hue="cyl", data=df_select, height=7, aspect=1...
read_csv("./datasets/mpg_ggplot2.csv") cyl_colors = {4: 'tab:red', 5: 'tab:green', 6: 'tab:blue', 8: 'tab:orange'} df_raw['cyl_color'] = df_raw.cyl.map(cyl_colors) # Mean and Median city mileage by make df = df_raw[['cty', 'manufacturer']].groupby('manufacturer'...
微信自动化：wechatpy 3、自动化数据服务，主要是提供流式数据服务，从数据获取、数据处理、数据建模、...
X, y = make_classification( n_samples=1000, n_features=2, n_redundant=0, n_clusters_per_class=1, weights=[0.05], random_state=42)df = pd.concat([pd.DataFrame(X), pd.Series(y)], axis=1)df.columns = ['x1', 'x2', 'y']plot(df=df, x1='x1', x2='x2...
df=pd.read_excel("E:/First.xlsx","Sheet1") 可视化为直方图 代码语言:javascript 代码运行次数:0 运行 AI代码解释 fig=plt.figure()#Plotsinmatplotlib reside within a figure object,use plt.figure to createnewfigure#Create one or more subplots using add_subplot,because you can't create blank figu...
from sklearn.datasets import make_circles from matplotlib import pyplot from pandas import DataFrame # generate 2d classification dataset X, y = make_circles(n_samples=100, noise=0.05)# scatter plot, dots colored by class value df = DataFrame(dict(x=X[:,0], y=X[:,1], label=y))color...
df_train = data[['Date','Close']] df_train = df_train.rename(columns={"Date":"ds","Close":"y"}) m = Prophet() m.fit(df_train) future = m.make_future_dataframe(periods=period) forecast = m.predict(future) # Show and plot foreca...
from sklearn.cluster import KMeansfrom sklearn.datasets import make_blobs # 生成模拟数据集import matplotlib.pyplot as plt 2. 生成模拟数据集 为了演示,我们首先生成一个模拟的数据集,通常在真实场景中,你会有自己的数据集。 # 生成带有3个聚类中心的数据集X, _ = make_blobs(n_samples=300, centers=...
sns.set_style('whitegrid')sns.countplot(x='target',data=df,palette='RdBu_r')plt.show() 数据处理 探索数据集后,我发现我需要在训练机器学习模型之前将一些分类变量转换为虚拟变量并缩放所有值。 首先,我将使用该 get_dummies 方法为分类变量创建虚拟列。
from .preprocessing import scale_data from .makedata import preprocess_data 同一个包的模块可以导入到另一个模块中使用。另一个名为makedata.py的模块将被添加进目录中，该模块使用preprocessing.py模块执行数据转换，然后将最终数据集导出为CSV文件，供后续使用。import preprocessing as pr import pandas as pd ...