Core building blocks across Javascript, PHP, C++, Java, Python, and Ruby: Ref: https://codesensei.medium.com/core-building-blocks-and-which-programming-language-to-study-first-446977d119a8

Click on the images to see them clearly

#!/usr/bin/env python

coding: utf-8

In[1]:

k-means clustering

from numpy import unique
from numpy import where
from sklearn.datasets import make_classification
from sklearn.cluster import KMeans
from matplotlib import pyplot
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
get_ipython().run_line_magic(‘matplotlib’, ‘inline’)
import pandas as pd
import numpy as np
import numpy as np
from sklearn.cluster import KMeans
from sklearn import datasets
from sklearn.preprocessing import StandardScaler

In[2]:

import warnings
warnings.filterwarnings(‘ignore’)

In[3]:

the combined data

data_folder = ‘./nhanes_input_data/’

import the CSV as a pandas dataframe

df = pd.read_csv( data_folder + ‘0_dietaryIntakeDataForClassificationAndAnalysisData.csv’)
df.shape

In[4]:

df.head(5)

In[5]:

parameters to be used for KMeans clustring: centres

X and/or kdf will have only features we want to create cluster around

kdf = df[
   
    [
        'RIDAGEYR_Age_in_years_at_screening'
        ,'URDACT_Albumin_creatinine_ratio_mg_g'
    ]
]
X = kdf
X[:5]

In[6]:

ref: internet (not my code, using as a library)

def clean_dataset(df):
assert isinstance(df, pd.DataFrame), "df needs to be a pd.DataFrame"
df.dropna(inplace=True)
indices_to_keep = ~df.isin([np.nan, np.inf, -np.inf]).any(1)
return df[indices_to_keep].astype(np.float64)

In[7]:

X has the features to cluster around (centres: Age, ACR). df has the complete data

after clustering is done using features in X, we find positions (index) for each data

in a cluster then we use those index positions to cluster the data from df

X.shape, df.shape

In[8]:

X = clean_dataset(X)

In[9]:

define the model

model = KMeans(n_clusters = 10) #,random_state=0, n_init="auto"

fit the model

model.fit(X)
#model.labels_

In[10]:

Create csv files with the cluster daya

One csv for one Cluster

In[11]:

howManyClusters = 10
for clusterId in range (howManyClusters):
ind_list = np.where(model.labels_ == clusterId )[0]
cluster = df.iloc[ind_list]
cluster.to_csv(‘./nhanes_output_data/classifiedGroups/kmeanscluster/cluster-‘
+ str(clusterId) + ‘.csv’);

In[12]:

model.cluster_centers_

In[13]:

Scatter plot to see each cluster points visually

std_data = StandardScaler().fit_transform(X)
plt.scatter(std_data[:,0], std_data[:,1], c = model.labels_, cmap = "rainbow")
plt.title("K-means Clustering of Diet and ACR data")
plt.show()

# References:

# print("Shape of cluster:", model.cluster_centers_.shape)

# https://stackoverflow.com/questions/50297142/get-cluster-points-after-kmeans-in-a-list-format

#

# https://machinelearningmastery.com/clustering-algorithms-with-python/

# https://stackoverflow.com/questions/50297142/get-cluster-points-after-kmeans-in-a-list-format

# https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html

# https://datascience.stackexchange.com/questions/48693/perform-k-means-clustering-over-multiple-columns

# https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html

#

>>> from sklearn.cluster import KMeans

>>> import numpy as np

>>> X = np.array([[1, 2], [1, 4], [1, 0],

… [10, 2], [10, 4], [10, 0]])

>>> kmeans = KMeans(n_clusters=2, random_state=0, n_init="auto").fit(X)

>>> kmeans.labels_

array([1, 1, 1, 0, 0, 0], dtype=int32)

>>> kmeans.predict([[0, 0], [12, 3]])

array([1, 0], dtype=int32)

>>> kmeans.cluster_centers_

array([[10.,  2.],

[ 1.,  2.]])

In[ ]:

Raise Error in Oracle

RAISE VALUE_ERROR;

Raise Application Error in Oracle

Create custom exception and raise it.

Handle Exception

You could also insert into error log table and RAISE

Reference:
https://blogs.oracle.com/connect/post/error-management

"Collaboration diagrams (known as Communication Diagram in UML 2.x) are used to show how objects interact to perform the behavior of a particular use case, or a part of a use case. Along with sequence diagrams, collaboration are used by designers to define and clarify the roles of the objects that perform a particular flow of events of a use case. They are the primary source of information used to determining class responsibilities and interfaces."

Ref: Check Below

https://www.visual-paradigm.com/servlet/editor-content/guide/uml-unified-modeling-language/what-is-uml-collaboration-diagram/sites/7/2018/12/collaboration-diagram-example.png

https://www.visual-paradigm.com/guide/uml-unified-modeling-language/what-is-uml-collaboration-diagram/

Ref: Software Engineering Course: https://www.cs.ox.ac.uk/people/michael.wooldridge/teaching/soft-eng/
https://www.cs.ox.ac.uk/people/michael.wooldridge/teaching/soft-eng/lect07-4up.pdf

How it works: if, elsif, else (then) (Click on the images to see them clearly)

Ref: https://docs.oracle.com/cd/B13789_01/appdev.101/b10807/13_elems024.htm

Example:

Ref: https://docs.oracle.com/cd/B13789_01/appdev.101/b10807/13_elems024.htm

Oracle: CASE, WHEN, THEN

Simple:

Searched:
”
Else:

Reverse For Loop

Ref: For Loop Examples in Oracle

https://docs.oracle.com/cd/E11882_01/appdev.112/e25519/controlstatements.htm#BABEFFDC

Oracle While Loop

While loop example from the referenced url

DECLARE
done BOOLEAN := FALSE;
BEGIN
WHILE done LOOP
DBMS_OUTPUT.PUT_LINE (‘This line does not print.’);
done := TRUE; — This assignment is not made.
END LOOP;

WHILE NOT done LOOP
DBMS_OUTPUT.PUT_LINE (‘Hello, world!’);
done := TRUE;
END LOOP;
END;
/

Ref: https://docs.oracle.com/en/database/oracle/oracle-database/19/lnpls/plsql-control-statements.html#GUID-3F69F563-BCAE-4D3E-8E03-F53C8D64D093

An unconstrained subtype has the same set of values as its base type, so it is only another name for the base type.

Syntax:

SUBTYPE subtype_name IS base_type

Example:

SUBTYPE "DOUBLE PRECISION" IS FLOAT

SUBTYPE Balance IS NUMBER;

Constrained SubType

SUBTYPE Balance IS NUMBER(8,2);

Oracle Exception Block Example:

Ref: https://docs.oracle.com/cd/B13789_01/appdev.101/b10807/07_errs.htm

Ref: https://docs.oracle.com/cd/B13789_01/appdev.101/b10807/02_funds.htm

https://stackoverflow.com/questions/7425153/reason-why-oracle-is-case-sensitive

Oracle Data Types and Allowed Sizes:

https://docs.oracle.com/cd/E11882_01/appdev.112/e25519/datatypes.htm#LNPLS99943

Oracle SIMPLE_FLOAT vs SIMPLE_DOUBLE

Ref: https://docs.oracle.com/cd/B28359_01/appdev.111/b28370/datatypes.htm#CJAEAEJG

PLS_Integer vs Number

"The PLS_INTEGER data type has these advantages over the NUMBER data type and NUMBER subtypes:

• PLS_INTEGER values require less storage.
• PLS_INTEGER operations use hardware arithmetic, so they are faster than NUMBER operations,

"

Ref: https://docs.oracle.com/cd/E11882_01/appdev.112/e25519/datatypes.htm#LNPLS319

Hardly anything is by me. All are from external sources. Credit belongs to them.