如何在jupyter笔记本中并排渲染两个pd.DataFrame？

Question

有没有一种简单的方法可以在 Jupyter 笔记本中快速并排查看两个 pd.DataFrame 的内容？

df1 = pd.DataFrame([(1,2),(3,4)], columns=['a', 'b'])
df2 = pd.DataFrame([(1.1,2.1),(3.1,4.1)], columns=['a', 'b'])
df1, df2

Answer 1

你应该尝试一下@Wes_McKinney 的这个功能

def side_by_side(*objs, **kwds):
    ''' Une fonction print objects side by side '''
    from pandas.io.formats.printing import adjoin
    space = kwds.get('space', 4)
    reprs = [repr(obj).split('\n') for obj in objs]
    print(adjoin(space, *reprs))


# building a test case of two DataFrame
import pandas as pd
import numpy as np


n, p = (10, 3)  # dfs' shape

# dfs indexes and columns labels
index_rowA = [t[0]+str(t[1]) for t in zip(['rA']*n, range(n))]
index_colA = [t[0]+str(t[1]) for t in zip(['cA']*p, range(p))]

index_rowB = [t[0]+str(t[1]) for t in zip(['rB']*n, range(n))]
index_colB = [t[0]+str(t[1]) for t in zip(['cB']*p, range(p))]

# buliding the df A and B
dfA = pd.DataFrame(np.random.rand(n,p), index=index_rowA, columns=index_colA)
dfB = pd.DataFrame(np.random.rand(n,p), index=index_rowB, columns=index_colB)

side_by_side(dfA,dfB)输出

          cA0       cA1       cA2              cB0       cB1       cB2
rA0  0.708763  0.665374  0.718613    rB0  0.320085  0.677422  0.722697
rA1  0.120551  0.277301  0.646337    rB1  0.682488  0.273689  0.871989
rA2  0.372386  0.953481  0.934957    rB2  0.015203  0.525465  0.223897
rA3  0.456871  0.170596  0.501412    rB3  0.941295  0.901428  0.329489
rA4  0.049491  0.486030  0.365886    rB4  0.597779  0.201423  0.010794
rA5  0.277720  0.436428  0.533683    rB5  0.701220  0.261684  0.502301
rA6  0.391705  0.982510  0.561823    rB6  0.182609  0.140215  0.389426
rA7  0.827597  0.105354  0.180547    rB7  0.041009  0.936011  0.613592
rA8  0.224394  0.975854  0.089130    rB8  0.697824  0.887613  0.972838
rA9  0.433850  0.489714  0.339129    rB9  0.263112  0.355122  0.447154