Question

import pandas as pd
import pandas.io.data as web
from pandas import Series, DataFrame
import matplotlib
import matplotlib.pyplot as plt
from numpy.random import randn
import numpy as np
matplotlib.style.use('ggplot')

stocks = {'xom': '2014-01-01', 'dvn': '2013-01-01', 'aapl': '2013-01-01'}

L = dict()

for stock, date in stocks.items():
    price = web.get_data_yahoo(stock, date)['Adj Close']
    change = price.diff().cumsum()
    perChange = change / price.iloc[0]
    L[stock] = perChange

df = pd.concat(L, axis=1)

df2 = df.describe()

如何格式化df2以使列为min，max，std等...并且行是股票代码？

Answer 1

使用日期框架的转置：DataFrame.T

df2 = df.describe().T # this is the equivalent of df.describe().transpose()

print df2
      count      mean       std       min       25%       50%       75%       max  
aapl    665  0.195720  0.331271 -0.284546 -0.089219  0.110605  0.501857  0.783157 
dvn     665  0.202538  0.143291 -0.246586  0.104409  0.175463  0.286709  0.548577  
xom     413 -0.049164  0.062285 -0.273573 -0.096234 -0.045035 -0.001124  0.060982

Answer 2

您要添加;

df2 = df2.transpose()

如何将数据框行调整为列

2 个答案: