pandas 熊猫，将 DataFrame 转换为 MultiIndex'ed DataFrame
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pandas, convert DataFrame to MultiIndex'ed DataFrame
提问by johnbaltis
I have a pandas.DataFramethat I want to convert to a MultiIndexed pandas.DataFrame.
我有一个pandas.DataFrame我想转换为MultiIndexed 的pandas.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 = pandas.concat((pandas.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)
Note that in this example I create what I wantand what I have.
请注意，在此示例中，我创建了我想要的和我拥有的.
So, IRL I would start with dfand want to turn it into df2(and don't have access to valsand result), how do I do this?
所以，我会从 IRL 开始df并想把它变成df2（并且无法访问vals和result），我该怎么做？
回答by jezrael
You need set_index:
你需要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
If need compare both DataFrames, need replace NaNto same values, else get False:
如果需要比较两者DataFrames，需要替换NaN为相同的值，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
