This is an alpha repo for EPF analysis tool
pip install -e git+https://github.com/gauravmeena0708/epftools#egg=epftools#!pip install -e git+https://github.com/gauravmeena0708/epf_tools2#egg=epftools2
import pandas as pd
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2, DataFrameStyler
df = pd.read_csv(<claim csv>)
COLUMNS = ['CLAIM ID', 'TASK ID', 'PENDING DAYS', 'STATUS', 'CLAIM TYPE']
RENAME_COLS ={
'CLAIM_ID':'CLAIM ID',
'ACC_TASK_ID':'TASK ID',
'STATUS':'STATUS',
'PEN_DAYS':'PENDING DAYS',
'FORM_TYPE_TEXT':'CLAIM TYPE'
}
df = df.rename(columns=RENAME_COLS)
processor = ClaimProcessor(10, 20)
df = processor.add_bins_and_categories(df)
elements = processor.get_elements_daily_summary(df, DataFrameStyler)
# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/report_06_02_24.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(elements,html=False)import pandas as pd
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2
df = pd.read_csv('data/claims.csv')
processor = ClaimProcessor(15, 20)
df = processor.add_bins_and_categories(df)
print(df.head())df1 = processor.get_flat_pivot(df,"GROUP","days_Group")
df2 = processor.get_flat_pivot(df,"GROUP","STATUS")
df3 = processor.get_flat_pivot(df,"GROUP","CATEGORY")
df4 = processor.get_flat_pivot(df,"GROUP","CLAIM TYPE")
df5 = processor.get_flat_pivot(df,"TASK","CATEGORY")
df6 = processor.get_flat_pivot(df,"TASK","STATUS")
dataframes =[df1,df2,df3,df4,df5,df6]pdf_generator = PDFGenerator(pdf_file="data/report.pdf")
pdf_generator.create_pdf(dataframes)# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/out.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(dataframes)from PIL import Image
import os, re, glob, base64
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2
def get_image_file_as_base64_data(file):
with open(file, 'rb') as image_file:
return base64.b64encode(image_file.read()).decode()
directory_path = "./"
pattern = re.compile(r"figure_\d+.png")
all_files = os.listdir(directory_path)
matching_files = [filename for filename in all_files if pattern.match(filename)]
dataframes=[]
for file in matching_files:
dataframes.append(f'<img src="data:;base64,{ get_image_file_as_base64_data(file) }">')
# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/out.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(dataframes, False)import pandas as pd
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2
df = pd.read_csv('data/claims.csv')
processor = ClaimProcessor(15, 20)
df = processor.add_bins_and_categories(df)
df1 = processor.get_flat_pivot(df, "days_Group", "GROUP")
df2 = processor.get_flat_pivot(df, "STATUS", "GROUP")
# Define style function for cell formatting
def highlight_min(s, color='green'):
is_max = s == s.min()
attr = 'background-color: {}'.format(color)
return [attr if v else '' for v in is_max]
def highlight_max(s, color='yellow'):
is_max = s == s.max()
attr = 'background-color: {}'.format(color)
return [attr if v else '' for v in is_max]
def highlight_top3(s, color='darkorange'):
top3_values = s.nlargest(3).index
is_top3 = s.index.isin(top3_values)
attr = 'color: {};font-weight: bold;'.format(color)
return [attr if v else '' for v in is_top3]
def conditional_color(val,cutoff=100,color = 'red'):
color = color if val > cutoff else "black"
return f"color: {color}"
def color_quantile(s, color='red'):
quantile_4_threshold = s.quantile(0.75)
is_in_quantile_4 = s >= quantile_4_threshold
attr = 'background-color: {}'.format(color)
return [attr if v else '' for v in is_in_quantile_4]
"""\
.map(conditional_color,cutoff=2000, color='red',subset = pd.IndexSlice[u[:-1], ['0-15']])\
.map(conditional_color,cutoff=400, color='red',subset = pd.IndexSlice[u[:-1], ["16-20"]]) \
.map(conditional_color,cutoff=10, color='red',subset = pd.IndexSlice[u[:-1], [">20"]])
"""
def get_styled(df):
u = df.index.get_level_values(0)
cols = df.columns
df_styled = df.style.apply(highlight_top3,color='orangered',subset = pd.IndexSlice[u[:-1], cols[:-1]],axis=1) \
.apply(color_quantile,color='khaki',subset = pd.IndexSlice[u[:-1], cols[:-1]],axis=1)
return df_styled
df1_styled = get_styled(df1)
df2 = get_styled(df2)
# Display the styled DataFrame
display(df1_styled)import os, re, base64
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2
def get_image_file_as_base64_data(file):
with open(file, 'rb') as image_file:
return base64.b64encode(image_file.read()).decode()
directory_path = "./"
pattern = re.compile(r"figure_\d+.png")
all_files = os.listdir(directory_path)
matching_files = [filename for filename in all_files if pattern.match(filename)]
elements=[]
elements.append(df1_styled.to_html())
elements.append(df2.to_html())
for file in matching_files:
elements.append(f'<img src="data:;base64,{ get_image_file_as_base64_data(file) }">')
# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/out.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(elements,html=False)#!pip install -e git+https://github.com/gauravmeena0708/epf_tools2#egg=epftools2
import pandas as pd
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2, DataFrameStyler
df = pd.read_csv('data/claims_26_12_23.csv')
processor = ClaimProcessor(10, 20)
df = processor.add_bins_and_categories(df)
def info(df):
display(df.head())
print(df['CATEGORY'].unique())
print(df['CLAIM TYPE'].unique())
print(df['INT_CATEGORY'].unique())
print(df['STATUS2'].unique())
info(df)
elements = processor.get_elements_daily_summary(df, DataFrameStyler)
# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/out.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(elements,html=False)
import os
import re
import base64
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2
from glob import glob
matching_files = glob(os.path.join("./data/", "figure_*.png"))
print(matching_files)
def get_image_file_as_base64_data(file_path):
with open(file_path, 'rb') as image_file:
return base64.b64encode(image_file.read()).decode()
def generate_html_elements(matching_files):
elements=[]
image_elements = map(lambda f: f'<img src="data:;base64,{get_image_file_as_base64_data(f)}">', matching_files)
elements.extend(list(image_elements))
return elements
html_template_path = 'data/template.html'
output_pdf_path = 'data/out.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
elements = generate_html_elements(matching_files)
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(elements, html=False)from epftools import PDFTools as pt
input_path = "in.pdf"
output_path_template = "output_{0}_{1}.pdf"
page_ranges = [(1, 1), (2, 2), (3, 4), (5, 5), (6, 6), (7, 7), (8, 8), (9, 9), (10, 11), (12, 12), (13, 13), (14, 14), (15, 15), (16, 16), (17, 17), (18, 18)]
pt.split_pdf(input_path, output_path_template, page_ranges)from epftools import ExcelMerger
folder_path = './/due2//'
merger = ExcelMerger(folder_path,ext=".xls")
merger.merge_and_save()!pip install -e git+https://github.com/gauravmeena0708/epftools#egg=epftools
!pip install epftools
!pip install reportlab pdfkit PyPDF2 pytesseract pdf2image
from epftools import PeriodicityProcessor
import pandas as pd
path24 = '<path>'
processor = PeriodicityProcessor(path24, '2023-12')
dall = processor.df
dall.head()
dall2 = pd.DataFrame(columns=['text_column', 'blank', 'reason1', 'reason2', 'reason_category'])
dall2[['blank', 'reason1', 'reason2']] = dall['REJECT_REASON'].str.split(r'\d\)', n=2, expand=True)
dall['reason1'] = dall2['reason1'].str.strip()
dall['reason2'] = dall2['reason2'].str.strip()
death10d = dall[dall['FORM_NAME']=="Death-10D"]
display(len(death10d))
display(death10d.head())
df2 = processor.col_grouped_rejection(dall,"GROUP_ID")#!pip install -e git+https://github.com/gauravmeena0708/epf_tools2#egg=epftools2
import pandas as pd
from epftools import ClaimProcessor, PDFGenerator, PDFGenerator2, DataFrameStyler
df = pd.read_csv('data/claims_06_02_24.csv')
COLUMNS = ['CLAIM ID', 'TASK ID', 'PENDING DAYS', 'STATUS', 'CLAIM TYPE']
RENAME_COLS ={
'CLAIM_ID':'CLAIM ID',
'ACC_TASK_ID':'TASK ID',
'STATUS':'STATUS',
'PEN_DAYS':'PENDING DAYS',
'FORM_TYPE_TEXT':'CLAIM TYPE'
}
df = df.rename(columns=RENAME_COLS)
processor = ClaimProcessor(10, 20)
df = processor.add_bins_and_categories(df)
elements = processor.get_elements_daily_summary(df, DataFrameStyler)
# Example usage:
html_template_path = 'data/template.html'
output_pdf_path = 'data/report_06_02_24.pdf'
wkhtmltopdf_path = r'C:\Program Files\wkhtmltopdf\bin\wkhtmltopdf.exe'
pdf_generator = PDFGenerator2(html_template_path, output_pdf_path, wkhtmltopdf_path)
pdf_generator.generate_pdf(elements,html=False)