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Convert pandas to numpy.ndarray for sparse.hstack


Convert pandas to numpy.ndarray for sparse.hstack

By : Nani S
Date : November 20 2020, 11:01 PM
should help you out I try to solve next problem , I've done as below. It works
code :
import numpy as np
import pandas as pd
from scipy import sparse

X1 = sparse.rand(10, 10000)
df = pd.DataFrame({ 'a': range(10)})

X2 = df['a'].reset_index()
X2 = X2.iloc[:,[1]].values

X = sparse.hstack((X1,X2))


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Convert 2D numpy.ndarray to pandas.DataFrame

Convert 2D numpy.ndarray to pandas.DataFrame


By : Anwaar
Date : March 29 2020, 07:55 AM
I hope this helps . I suspect your ndarr, if expressed as a 2d np.array, always has the shape of n,m, where n is the length of cache1.id1 and m is the length of cache2.id2. And the last entry in cache2, should be {'id2': 38472837} instead of {'id': 38472837}. If so, the following simple solution may be all what is needed:
code :
In [30]:

df=pd.DataFrame(np.array(ndarr).ravel(),
             index=pd.MultiIndex.from_product([cache1.id1.values, cache2.id2.values],names=['idx1', 'idx2']),
             columns=['val'])
In [33]:

print df.reset_index()
       idx1      idx2  val
0   ABC1234   3276827  4.3
1   ABC1234  98567498  5.6
2   ABC1234  38472837  6.7
3  NCMN7838   3276827  3.2
4  NCMN7838  98567498  4.5
5  NCMN7838  38472837  2.1

[6 rows x 3 columns]
Convert a numpy.ndarray to string(or bytes) and convert it back to numpy.ndarray

Convert a numpy.ndarray to string(or bytes) and convert it back to numpy.ndarray


By : user3621682
Date : March 29 2020, 07:55 AM
To fix this issue I'm having a little trouble here, , You can use the fromstring() method for this:
code :
arr =np.array([1,2,3,4,5,6])
ts = arr.tostring()
print np.fromstring(ts,dtype=int)

>>>[1 2 3 4 5 6]
Convert pandas nested Series into Numpy ndarray

Convert pandas nested Series into Numpy ndarray


By : user3486564
Date : March 29 2020, 07:55 AM
I wish did fix the issue. I have a pandas DataFrame that looks like this: , Try this, it should strip the brackets and create the double array:
code :
def reshape_array_string(x):
    temp = x.replace('[', '').replace(']','').replace(',','').split(" ")
    shapelen = len(temp)//2
    return (np.reshape(temp, [shapelen,2])) 

df['Count'].apply(reshape_array_string)
0              [[20.0, 38.5], [3.2, 8.5]]
1    [[3.7, 8.2], [5.7, 5.5], [4.6, 2.2]]

Convert pandas sparse dataframe to sparse numpy matrix for sklearn use?

Convert pandas sparse dataframe to sparse numpy matrix for sklearn use?


By : scottM
Date : March 29 2020, 07:55 AM
To fix the issue you can do You should be able to use the experimental .to_coo() method in pandas [1] in the following way:
keras : converting numpy ndarray of strings to numpy ndarray of floats :: ValueError: could not convert string to float:

keras : converting numpy ndarray of strings to numpy ndarray of floats :: ValueError: could not convert string to float:


By : nallen718
Date : March 29 2020, 07:55 AM
it fixes the issue Assuming that the Y values are intended to be 'yes'/1...
Use numpy.where to cast the 'Y' values to 1:
code :
X = np.where(X=='Y', 1, X)
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