def plot_varying_funds(最低本金, 最高本金, 还钱总数, 周期数): style.use('ggplot') plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False x = np.linspace(最低本金, 最高本金, 10) x = [round(x_i, 1) for x_i in x] y = [calc_interest(x_i, 还钱总数, 周期数) for x_i in x] plt.plot(x, y) plt.xlabel('本金') plt.ylabel('周期利率(百分比)') plt.legend() plt.show()
# coding: utf-8 # In[1]: get_ipython().magic('matplotlib inline') import pandas as pd import pandas_datareader import datetime import matplotlib.pylab as plt import seaborn as sns from matplotlib.pylab import style from statsmodels.tsa.arima_model import ARIMA from statsmodels.graphics.tsaplots import plot_acf, plot_pacf style.use('ggplot') plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False # In[2]: stockFile = 'data/T10yr.csv' stock = pd.read_csv(stockFile, index_col=0, parse_dates=[0]) stock.head(10) # In[77]:
pip3 uninstall pandas_datareader pip3 install pandas_datareader==0.5.0 #高版本有bug, 降回低版本 作者: 梁斌 版本: 1.0 日期: 2017/02/18 项目名称: 股票数据分析 """ import pandas as pd import pandas_datareader import datetime import matplotlib.pylab as plt from matplotlib.pylab import style from statsmodels.tsa.arima_model import ARIMA from statsmodels.graphics.tsaplots import plot_acf, plot_pacf style.use('ggplot') # 设置图片显示的主题样式 # 解决matplotlib显示中文问题 plt.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体 plt.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题 def run_main(): """ 主函数 """ # 1. 准备数据 # 指定股票分析开始日期 start_date = datetime.datetime(2007, 1, 1) # 指定股票分析截止日期 end_date = datetime.datetime(2017, 3, 1)
from sklearn.linear_model import LogisticRegression from sklearn.model_selection import cross_validate from sklearn.model_selection import KFold from sklearn.model_selection import train_test_split from sklearn.model_selection import cross_val_score from sklearn.metrics import accuracy_score from sklearn.feature_selection import SelectKBest, f_classif, chi2 from sklearn.ensemble import GradientBoostingClassifier from sklearn.ensemble import RandomForestClassifier from sklearn.ensemble import RandomForestRegressor from operator import itemgetter import re import warnings warnings.filterwarnings("ignore") style.use('seaborn') plt.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False # In[202]: # Load dataset and view the table titanic = pd.read_csv( "/Users/liliang/Desktop/machine learning/Titanic/train.csv") titanic.head(5).style # In[203]: # Examine the data titanic.describe().style