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XAIL Data quality

Project description

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"

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()

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