xurpas-data-quality 1.1.0

XAIL Data quality

Xurpas Data Quality Report

How to Use

• Load the data to be analyzed (so far only csv files supported)
• Import the DataReport class
• Save the report to html File

DataReport

Creates and saves to file the data report.

Args

file:       The path of the file you want to analyze. If empty, df parameter must exist.
         Only supports .csv, .xlsx, .parquet, and .orc file formats.
df:       Pandas DataFrame object of data to be analyzed, If using df, file must be empty.
report_name:   Name of the report. Defaults to 'Data Report'.
file_path:     Path/ directory of where the report is to be saved.
data_types:    A dict containing the column names and column type to specify column data type.          Data Types currently allowed "Categorical, Float, Integer, Date, String".
minimal:     Default is False. A boolean to check if you want minimal mode as your data report.

Returns

HTML File of data quality Report

Sample Usage using pandas DataFrame

import pandas as pd
from xurpas_data_quality import DataReport

df = pd.read_csv("manhour_utilization_summary.csv")
report = DataReport(df=df,
                    report_name="Manhour Utilization Summary", 
                    file_path="test_reports/test.html")
report.to_file()

Sample Usage using filepath

from xurpas_data_quality import DataReport
report = DataReport(file="manhour_utilization_summary.csv",
                    report_name="Manhour Utilization Summary", 
                    file_path="test_reports/test.html")
report.to_file()