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https://github.com/sotte/pydata_eda_lightning_talk

Last synced: 7 days ago
JSON representation

Host: GitHub
URL: https://github.com/sotte/pydata_eda_lightning_talk
Owner: sotte
License: mit
Created: 2018-07-08T15:27:32.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2018-07-12T15:48:22.000Z (over 6 years ago)
Last Synced: 2024-08-02T15:10:36.659Z (3 months ago)
Language: HTML
Size: 156 KB
Stars: 4
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.ipynb
- License: LICENSE

Awesome Lists containing this project

README

{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Little helpers to ease EDA\n",
"EDA, albeit very time consuming, is a very important part of every DS task.\n",
"Lately I've been using these great tools that ease EDA.\n",
"Check them out.\n",
"\n",
"- [missingno](https://github.com/ResidentMario/missingno)\n",
"- [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling)\n",
"- [great_expectations](https://github.com/great-expectations/great_expectations)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Init"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import json\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# missingno\n",
"> Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities that allows you to get a quick visual summary of the completeness (or lack thereof) of your dataset.\n",
"> Just pip install missingno to get started.\n",
"> -- https://github.com/ResidentMario/missingno"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from quilt.data.ResidentMario import missingno_data\n",
"\n",
"\n",
"collisions = missingno_data.nyc_collision_factors()\n",
"collisions = collisions.replace(\"nan\", np.nan)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import missingno as msno\n",
"\n",
"\n",
"msno.matrix(collisions.sample(250))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# pandas_profiling\n",
"> Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great but a little basic for serious exploratory data analysis.\n",
"> --https://github.com/pandas-profiling/pandas-profiling"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from pandas_profiling import ProfileReport"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"data_v1.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"report = ProfileReport(df)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"report.to_file(\"report_v1.html\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# great_expectations\n",
"> Great Expectations is a framework that helps teams save time and promote analytic integrity with a new twist on automated testing: pipeline tests. Pipeline tests are applied to data (instead of code) and at batch time (instead of compile or deploy time).\n",
"> -- https://github.com/great-expectations/great_expectations"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"import great_expectations as ge"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"great_expectations.dataset.pandas_dataset.PandasDataset"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = ge.from_pandas(df)\n",
"\n",
"type(df)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"

\n",
"\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"\n",
"\n",
" \n",
" \n",
" \n",
" SepalLength\n",
" SepalWidth\n",
" PetalLength\n",
" PetalWidth\n",
" Name\n",
" \n",
" \n",
" \n",
" \n",
" 0\n",
" 5.1\n",
" 3.5\n",
" 1.4\n",
" 0.2\n",
" Iris-setosa\n",
" \n",
" \n",
" 1\n",
" 4.9\n",
" 3.0\n",
" 1.4\n",
" 0.2\n",
" Iris-setosa\n",
" \n",
" \n",
" 2\n",
" 4.7\n",
" 3.2\n",
" 1.3\n",
" 0.2\n",
" Iris-setosa\n",
" \n",
" \n",
" 3\n",
" 4.6\n",
" 3.1\n",
" 1.5\n",
" 0.2\n",
" Iris-setosa\n",
" \n",
" \n",
" 4\n",
" 5.0\n",
" 3.6\n",
" 1.4\n",
" 0.2\n",
" Iris-setosa\n",
" \n",
" \n",
"\n",
"

"
],
"text/plain": [
" SepalLength SepalWidth PetalLength PetalWidth Name\n",
"0 5.1 3.5 1.4 0.2 Iris-setosa\n",
"1 4.9 3.0 1.4 0.2 Iris-setosa\n",
"2 4.7 3.2 1.3 0.2 Iris-setosa\n",
"3 4.6 3.1 1.5 0.2 Iris-setosa\n",
"4 5.0 3.6 1.4 0.2 Iris-setosa"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'], dtype=object)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.Name.unique()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'success': True,\n",
" 'result': {'element_count': 150,\n",
" 'missing_count': 0,\n",
" 'missing_percent': 0.0,\n",
" 'unexpected_count': 0,\n",
" 'unexpected_percent': 0.0,\n",
" 'unexpected_percent_nonmissing': 0.0,\n",
" 'partial_unexpected_list': []}}"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.expect_column_values_to_be_in_set(\n",
" \"Name\",\n",
" set(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica']),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'success': True,\n",
" 'result': {'observed_value': 0.1,\n",
" 'element_count': 150,\n",
" 'missing_count': 0,\n",
" 'missing_percent': 0.0}}"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.expect_column_min_to_be_between(\n",
" \"PetalWidth\",\n",
" min_value=0.1,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# there are many, many expectations!\n",
"# and you can write your own!"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'results': [{'success': True,\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_to_exist',\n",
" 'kwargs': {'column': 'SepalLength', 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_to_exist',\n",
" 'kwargs': {'column': 'SepalWidth', 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_to_exist',\n",
" 'kwargs': {'column': 'PetalLength', 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_to_exist',\n",
" 'kwargs': {'column': 'PetalWidth', 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_to_exist',\n",
" 'kwargs': {'column': 'Name', 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'result': {'element_count': 150,\n",
" 'missing_count': 0,\n",
" 'missing_percent': 0.0,\n",
" 'unexpected_count': 0,\n",
" 'unexpected_percent': 0.0,\n",
" 'unexpected_percent_nonmissing': 0.0,\n",
" 'partial_unexpected_list': []},\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_values_to_be_in_set',\n",
" 'kwargs': {'column': 'Name',\n",
" 'values_set': ['Iris-setosa', 'Iris-virginica', 'Iris-versicolor'],\n",
" 'result_format': 'BASIC'}}},\n",
" {'success': True,\n",
" 'result': {'observed_value': 0.1,\n",
" 'element_count': 150,\n",
" 'missing_count': 0,\n",
" 'missing_percent': 0.0},\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_min_to_be_between',\n",
" 'kwargs': {'column': 'PetalWidth',\n",
" 'min_value': 0.1,\n",
" 'result_format': 'BASIC'}}}]}"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.validate()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"WARNING: get_expectations_config discarded\n",
"\t0 failing expectations\n",
"\t7 result_format kwargs\n",
"\t0 include_configs kwargs\n",
"\t0 catch_exceptions kwargs\n",
"If you wish to change this behavior, please set discard_failed_expectations, discard_result_format_kwargs, discard_include_configs_kwargs, and discard_catch_exceptions_kwargs appropirately.\n"
]
}
],
"source": [
"df.save_expectations_config(\"expectations.json\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load and validate new data"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'results': []}"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with open(\"expectations.json\") as f:\n",
" expectations = json.load(f)\n",
"\n",
"df_v2 = ge.read_csv(\n",
" \"data_v1.csv\",\n",
" expectations_config=expectations,\n",
")\n",
"df_v2.validate(only_return_failures=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'results': []}"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ge.validate(\n",
" pd.read_csv(\"data_v1.csv\"),\n",
" expectations_config=expectations,\n",
" only_return_failures=True,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load and validate \"unexpected data\""
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(\"data_v1.csv\")\n",
"df.loc[0, \"PetalWidth\"] = 0"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'results': [{'success': False,\n",
" 'result': {'observed_value': 0.0,\n",
" 'element_count': 150,\n",
" 'missing_count': 0,\n",
" 'missing_percent': 0.0},\n",
" 'exception_info': {'raised_exception': False,\n",
" 'exception_message': None,\n",
" 'exception_traceback': None},\n",
" 'expectation_config': {'expectation_type': 'expect_column_min_to_be_between',\n",
" 'kwargs': {'column': 'PetalWidth', 'min_value': 0.1}}}]}"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ge.validate(\n",
" df,\n",
" expectations_config=expectations,\n",
" only_return_failures=True,\n",
")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}