initial commit vers 2

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+dataset.csv filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,78 @@
+#          imports
+# ====================================
+
+import numpy as np
+import pandas as pd
+import seaborn as sns
+from random import randint
+import matplotlib.pyplot as plt
+import streamlit as st
+import streamlit.components.v1 as components
+
+#from sklearn.linear_model import LogisticRegression
+#from sklearn.svm import SVC
+#from sklearn.neighbors import KNeighborsClassifier
+#from sklearn.tree import DecisionTreeClassifier
+#from sklearn.ensemble import RandomForestClassifier
+
+#from sklearn.model_selection import train_test_split
+#from sklearn.model_selection import StratifiedKFold
+#from imblearn.pipeline import make_pipeline as imbalanced_make_pipeline
+#from imblearn.over_sampling import SMOTE
+#from sklearn.model_selection import RandomizedSearchCV
+#from sklearn.metrics import classification_report, confusion_matrix, f1_score,accuracy_score, precision_score, recall_score, roc_auc_score
+
+#from sklearn.feature_selection import SelectKBest
+#from sklearn.feature_selection import f_classif
+
+#import warnings
+#warnings.filterwarnings("ignore")
+
+#       load upper
+# ==================================
+
+components.html(
+    """
+        <a href="https://git.io/typing-svg"><img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&pause=1000&width=435&lines=Анализ+банкротства+компании" alt="Typing SVG" /></a>
+        <a href="https://git.io/typing-svg"><img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&pause=1000&width=435&lines=методами+искуственного+интеллекта" alt="Typing SVG" /></a>
+    """
+)
+
+st.markdown("<h1 style='text-align: center;'>Применение методов машинного обучения в анализе банкротства</h1>", unsafe_allow_html=True)
+
+components.html(
+    """
+        <img src="https://fincult.info/upload/als-property-editorblock/4a2/4a278980ab4958de5e75aa5290842d77.png" align="center">
+    """
+)
+
+#with open("D:\dev\to_git\test_task_ranhigs\Company_bankruptcy_prediction\for_web\img.png", "rb") as f:
+#    st.image(f.read(), use_column_width=True)
+
+with st.expander("ℹ️ - О приложении", expanded=True):
+
+    st.write(
+            """
+                -   Это приложение — это простой в использовании интерфейс, встроенный в специальную библиотеку Streamlit.
+                -   В том числе и сам алгоритм машинного обучения, который можно использовать через форму
+            """
+        )
+
+
+st.write(
+    """
+        # Краткое описание
+
+    """
+)
+
+#       cleaning data
+# ==================================
+
+data = pd.read_csv("D:\dev\to_git\test_task_ranhigs\Company_bankruptcy_prediction\for_web\dataset.csv")
+data.columns = [i.title().strip() for i in list(data.columns)]
+
+row = data.shape[0]
+col = data.shape[1]
+
+text = print("The number of rows within the dataset are {} and the number of columns is {}".format(row,col))

dataset.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:67bf2e7c75490f7ad3f76bbce57d49cdc25967cdab607527b94f944863fa14d8
+size 11456101