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
