python - 如何将数据框的行调整为列

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()

如何设置 df2 的格式，使列为 min、max、std 等...而行为股票代码？

Answer 1

使用日期帧的转置: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