pandas,将DataFrame转换为MultiIndex'ed DataFrame
问题描述:
我有一个pandas.DataFrame
,我想将其转换为MultiIndex
ed pandas.DataFrame
。pandas,将DataFrame转换为MultiIndex'ed DataFrame
import numpy
import pandas
import itertools
xs = numpy.linspace(0, 10, 100)
ys = numpy.linspace(0, 0.1, 20)
zs = numpy.linspace(0, 5, 200)
def func(x, y, z):
return x * y/z
vals = list(itertools.product(xs, ys, zs))
result = [func(x, y, z) for x, y, z in vals]
# Original DataFrame.
df = pandas.DataFrame(vals, columns=['x', 'y', 'z'])
df = pd.concat((pd.DataFrame(result, columns=['result']), df), axis=1)
# I want to turn `df` into this `df2`.
index = pandas.MultiIndex.from_tuples(vals, names=['x', 'y', 'z'])
df2 = pandas.DataFrame(result, columns=['result'], index=index)
注意,在这个例子中,我创建了我想和我有。
所以,IRL我将开始与df
,并希望把它变成df2
(而不必访问vals
和result
),我该怎么办呢?
答
您需要set_index
:
print (df2.head())
result
x y z
0.0 0.0 0.000000 NaN
0.025126 0.0
0.050251 0.0
0.075377 0.0
0.100503 0.0
print (df.set_index(['x','y','z']).head())
result
x y z
0.0 0.0 0.000000 NaN
0.025126 0.0
0.050251 0.0
0.075377 0.0
0.100503 0.0
如果需要比较这两个DataFrames
,需要更换NaN
到相同的值,否则得到False
:
print (df.set_index(['x','y','z']).eq(df2).all())
result False
dtype: bool
print (np.nan == np.nan)
False
print (df.fillna(1).set_index(['x','y','z']).eq(df2.fillna(1)).all())
result True
dtype: bool
美丽的,谢谢! – johnbaltis