Adding a value to the first index of a list of array by using a list comprehension Python

Question

The Vals list comprehension below modifies Values such that for the number of nth rows it indexes the array values as such. How would I be able to add an increment to the Vals list comprehension where it adds 100 in front of all of the modified lists? I want to only modify the list comprehension function to do that.

import numpy as np 

first_index_val = 100
Values = np.array([[130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72]])

Vals = np.array([arr[i:] for i,arr in enumerate(Values.tolist())])

Output:

[list([130.0, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([135.3, 139.05, 156.08, 163.88, 173.72])
 list([139.05, 156.08, 163.88, 173.72]) list([156.08, 163.88, 173.72])
 list([163.88, 173.72]) list([173.72])]

Expected Output:

[list([100, 130.0, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 139.05, 156.08, 163.88, 173.72]) list([100, 156.08, 163.88, 173.72])
 list([100, 163.88, 173.72]) list([100, 173.72])]

Just use [100] + arr[i:] in the list comprehension`

Mark
– Mark

2022-01-09 22:50:01 +00:00
Commented Jan 9, 2022 at 22:50 — Mark
– Mark, Commented Jan 9, 2022 at 22:50

Ganesh Budhathoki · Accepted Answer · 2022-01-10 00:54:30Z

1

Here is my take on it, simple and declarative.

import numpy as np

first_index_val = 100
values = np.array([[130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72]])

values = np.array([ [100] + arr[i:] for i, arr in enumerate(values.tolist())])
print(values)

edited Jan 10, 2022 at 0:54

answered Jan 9, 2022 at 23:31

Ganesh Budhathoki

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4 Comments

Ganesh Budhathoki Over a year ago

use your enumeration after the last flip

bull selcuk Over a year ago

Thanks for the solution but I still dont get the Expected Output when doing that. Even after the enumeration.

Ganesh Budhathoki Over a year ago

In that case, follow the solution posted by @Pepsi-Joe, only he misplaced the [100] it should be: np.array([ [100] + arr[i:] for i, arr in enumerate(values.tolist())])

Ganesh Budhathoki Over a year ago

I edited the code above to get the solution you want. Hope this helps.

Pepsi-Joe · Accepted Answer · 2022-01-10 02:10:04Z

0

Just add in the addition to the list comprehension.

Vals = np.array([[100] + arr[i:] for i,arr in enumerate(Values.tolist())])

edited Jan 10, 2022 at 2:10

answered Jan 9, 2022 at 22:50

Pepsi-Joe

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2 Comments

bull selcuk Over a year ago

the functionality for this code does not work

Pepsi-Joe Over a year ago

Yes, it seems that Numpy is not happy with having rows of different lengths. Do you need it in an array? it seems you want a list of lists. If you are okay with a list of lists, then just get rid of np.array in my answer.

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