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Sunday, 4 February 2018

27Th More on dist Final

27Th More on dist

Vlr Training

In [2]:
enames=["ramesh","kiran","rajesh"]
months=["jan","feb","march"]
In [3]:
enames
Out[3]:
['ramesh', 'kiran', 'rajesh']
In [5]:
ramesh=[30000,4000,3900]
In [6]:
kiran=[5000,2000,8000]
In [7]:
rajesh=[3000,20000,10000]
In [2]:
import numpy as np
In [11]:
sal=np.array([ramesh,kiran,rajesh])
In [12]:
sal
Out[12]:
array([[30000,  4000,  3900],
       [ 5000,  2000,  8000],
       [ 3000, 20000, 10000]])
In [13]:
print(sal)

[[30000  4000  3900]
 [ 5000  2000  8000]
 [ 3000 20000 10000]]
In [15]:
Out[15]:
'5000'
In [17]:
mat1[0,0]
Out[17]:
'30000'
In [14]:
denames={"ramesh":0,"kiran":1,"rajesh":2}
In [15]:
sal
Out[15]:
array([[30000,  4000,  3900],
       [ 5000,  2000,  8000],
       [ 3000, 20000, 10000]])
In [16]:
sal[0]
Out[16]:
array([30000,  4000,  3900])
In [18]:
sal[denames['ramesh']]
Out[18]:
array([30000,  4000,  3900])
In [19]:
dmonths={"jan":0,"feb":1,"march":2}
In [21]:
sal[denames['ramesh'],dmonths['jan']]
Out[21]:
30000
at

2 comments:

  1. littu2 December 2025 at 01:52

    Nice breakdown — the code example with arrays and indexing in this “More on dist” post is really helpful for understanding how data structures work with Python/Numpy. For folks balancing studies and coding practice, you might also look into sat coaching online by Fast Prep Academy.

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  2. ashwith17 March 2026 at 01:21

    This is a very insightful post explaining distributed systems concepts and their practical applications. Understanding these fundamentals is essential for anyone working in modern IT environments. As technology continues to evolve, gaining expertise in cloud-based data platforms is also becoming important. If you're interested in building skills in this area, you can check out this program: Snowflake Training in Hyderabad. It offers valuable hands-on learning for data professionals.

    ReplyDelete