Spaces:
Runtime error
Runtime error
# 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)) | |