plt.plot(return_data['AAPL'], return_data['MSFT'], 'r.') ax = plt.axis() x = np.linspace(ax[0], ax[1] + 0.01) plt.plot(x, model.params[0] + model.params[1] * x, 'b', lw=2) plt.grid(True) plt.axis('tight') plt.xlabel('Apple Returns') plt.ylabel('Microsoft retu...
financial_data['Date'] = pd.to_datetime(financial_data['Date']) financial_data.set_index('Date', inplace=True) # 技术分析 financial_data['SMA'] = ta.trend.sma_indicator(financial_data['Close'], window=20) # 数据可视化 plt.figure(figsize=(10, 6)) plt.plot(financial_data.index, fin...
折线图可以用来展示收入和支出随时间变化的趋势。 importmatplotlib.pyplotasplt# 绘制折线图plt.plot(data_transformed['Date'],data_transformed['Revenue'],label='Revenue')plt.plot(data_transformed['Date'],data_transformed['Expenses'],label='Expenses')# 添加标题和图例plt.title('Financial Performance')pl...
pip install yfinance --quiet# Importing libraries # Pandas & NumPy import pandas as pd import numpy as np # Yfinance to retrieve financial data import yfinance as yf # Plotly for Data Visualization import plotly.express as px import plotly.graph_objs as go import plotly.subplots as sp from ...
data = pd.read_excel('financial_data.xlsx', sheet_name='Sheet1') # 创建财务报表模板 report_template = { 'Department': [], 'Total Revenue': [], 'Total Expense': [], 'Net Income': [] } # 计算每个部门的财务数据 for department, group in data.groupby('Department'): ...
importpandasaspdimportmatplotlib.pyplotasplt# 读取金融数据data= pd.read_csv('financial_data.csv')# 数据预处理data['return'] =data['price'].pct_change# 计算累计收益率cumulative_return = (1+data['return']).cumprod# 绘制累计收益率曲线plt.plot(data.index, cumulative_return)plt.title('Cumulative...
df=pd.read_csv('financial_data.csv')# 数据清洗,去除重复数据 df.drop_duplicates(inplace=True)# 处理缺失值 df.fillna(0,inplace=True)# 格式转换 df['amount']=df['amount'].astype(float)df['date']=pd.to_datetime(df['date']) 2.2 数据可视化 ...
In [13]: data =np.arange(10) In [14]: data Out[14]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) In [15]: plt.plot(data) ▲图1 简单的线性图 尽管seaborn等库和pandas内建的绘图函数可以处理大部分绘图的普通细节,但如果你想在提供的函数选项之外进行定制则需要学习一些matplotlib的AIP...
finance.py is a collection of modules for collecting , collecting ,analying and plotting financial data.让我们先看一个example 关于利用matplotlib模块获取finance.yahoo.com里的历史数据并绘图,先贴代码 [python]view plain copy 1.from pylab import figure, show 2.from matplotlib.finance import quotes_hist...
print(data.head()) # 数据可视化 plt.plot(data.index, data['close']) plt.title('Shanghai Composite Index') plt.xlabel('Date') plt.ylabel('Price') plt.show() ``` 2. 统计分析和建模 实例:使用pandas进行财务分析,筛选出净利润增长率和ROE都高于行业平均水平的公司。