等效于将新行/列中的值添加到numpy中，就像R的data.frame

Question

In RI can do:

> y = c(2,3)
> x = c(4,5)
> z = data.frame(x,y)
> z[3,3]<-6
> z
   x  y V3
1  4  2 NA
2  5  3 NA
3 NA NA  6

R automatically fills the empty cells with NA. If I use numpy.insert from numpy , numpy throws by default an error:

import numpy

y = [2,3]
x = [4,5]
z = numpy.array([y, x])

z = numpy.insert(z, 3, 6, 3)

IndexError: axis 3 is out of bounds for an array of dimension 2

Is there a way to insert values in a way that works similar to R in numpy?

Answer 1

In numpy you need to initialize an array with the appropriate size:

z = numpy.empty(3, 3)
z.fill(numpy.nan)
z[:2, 0] = x
z[:2, 1] = z
z[3,3] = 6

Answer 2

如果您想在python中获得更像R的体验，我强烈建议您使用pandas ，这是一个基于numpy的更高级别的库，可以执行此类操作。

Answer 3

Looking at the raised error is possible to understand why it occurred: you are trying to insert values in an axes non existent in z .

you can fix it doing

import numpy as np
y = [2,3]
x = [4,5]
array = np.array([y, x])
z = np.insert(array, 1, [3,6], axis=1))

The interface is quite different from the R's one. If you are using IPython , you can easily access the documentation for some numpy function, in this case np.insert , doing:

help(np.insert)

which gives you the function signature, explain each parameter used to call it and provide some examples.

you could, alternatively do

import numpy as np
x = [4,5]
y = [2,3]
array = np.array([y,x])
z = [3,6]
new_array = np.vstack([array.T, z]).T  # or, as below
# new_array = np.hstack([array, z[:, np.newaxis])

Also, give a look at the Pandas module. It provides an interface similar to what you asked, implemented with numpy.

With pandas you could do something like:

import pandas as pd

data = {'y':[2,3], 'x':[4,5]}
dataframe = pd.DataFrame(data)
dataframe['z'] = [3,6]

which gives the nice output:

    x   y   z
0   4   2   3
1   5   3   5

Answer 4

numpy is more of a replacement for R's matrices, and not so much for its data frames. You should consider using python's pandas library for this. For example:

In [1]: import pandas

In [2]: y = pandas.Series([2,3])

In [3]: x = pandas.Series([4,5])

In [4]: z = pandas.DataFrame([x,y])

In [5]: z
Out[5]: 
   0  1
0  4  5
1  2  3

In [19]: z.loc[3,3] = 6

In [20]: z
Out[20]: 
    0   1   3
0   4   5 NaN
1   2   3 NaN
3 NaN NaN   6