.

Jenkinsfile

@@ -23,7 +23,7 @@ pipeline {
                     image.inside{
                         sh 'chmod +x preprocesing.py'
                         sh 'echo ${CUTOFF}'
-                        sh 'python3 preprocessing.py ${CUTOFF}'
+                        sh 'python3 preprocesing.py ${CUTOFF}'
                     }
                 }
             }

preprocesing_python.py

@@ -1,41 +0,0 @@
-import sys
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-
-sc = pd.read_csv('who_suicide_statistics.csv')
-
-train, validate, test = np.split(sc.sample(frac=1, random_state=42),
-                                 [int(.6*len(sc)), int(.8*len(sc))])
-
-print("Train set: ", train.size)
-print("Validate set: ", validate.size)
-print("Test set: ", test.size)
-print(train.describe(include='all'))
-print(train.country.value_counts())
-
-print(validate.describe(include='all'))
-print(validate.country.value_counts())
-
-print(test.describe(include='all'))
-print(test.country.value_counts())
-
-pd.value_counts(train['country']).plot.bar()
-pd.value_counts(validate['country']).plot.bar()
-pd.value_counts(test['country']).plot.bar()
-
-test['age'] = test['age'].map(lambda x: x.rstrip('years'))
-train['age'] = train['age'].map(lambda x: x.rstrip('years'))
-validate['age'] = validate['age'].map(lambda x: x.rstrip('years'))
-
-print(train.isnull().sum())
-print(validate.isnull().sum())
-print(test.isnull().sum())
-
-train.dropna(inplace=True)
-validate.dropna(inplace=True)
-test.dropna(inplace=True)
-
-print(train)
-print(validate)
-print(test)