{ "cells": [ { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "# US Immigration Data Lake\n", "### A source-of-truth database for decision making\n", "\n", "#### Project Summary\n", "We'll work with four datasets to complete the project. The main dataset will include data on immigration to the United States, and supplementary datasets will include data on airport codes, U.S. city demographics, and temperature data.\n", "\n", "The project follows the follow steps:\n", "* Step 1: Scope the Project and Gather Data\n", "* Step 2: Explore and Assess the Data\n", "* Step 3: Define the Data Model\n", "* Step 4: Run ETL to Model the Data\n", "* Step 5: Complete Project Write Up" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "editable": true }, "outputs": [], "source": [ "# Do all imports and installs here\n", "import os\n", "import pandas as pd, re\n", "from datetime import datetime\n", "from pyspark.sql import SparkSession\n", "from pyspark.sql.functions import udf" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "### Step 1: Scope the Project and Gather Data\n", "\n", "#### Scope \n", "The main deliverable of our work will be a data lake in the cloud that will support answering questions through analytics tables and dashboards.\n", "\n", "#### Describe and Gather Data \n", "For this work we have used the immigration, the global temperature and demographics datasets as well as the descriptions contained in the `I94_SAS_Labels_Descriptions.SAS` file. " ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### Immigration Data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "editable": true }, "outputs": [], "source": [ "immigration_fname = '../../data/18-83510-I94-Data-2016/i94_apr16_sub.sas7bdat'\n", "immigration = pd.read_sas(immigration_fname, 'sas7bdat', encoding=\"ISO-8859-1\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
cicidi94yri94moni94citi94resi94portarrdatei94modei94addrdepdatei94biri94visacountdtadfilevisapostoccupentdepaentdepdentdepumatflagbiryeardtaddtogenderinsnumairlineadmnumfltnovisatype
06.02016.04.0692.0692.0XXX20573.0NaNNaNNaN37.02.01.0NaNNaNNaNTNaNUNaN1979.010282016NaNNaNNaN1.897628e+09NaNB2
17.02016.04.0254.0276.0ATL20551.01.0ALNaN25.03.01.020130811SEONaNGNaNYNaN1991.0D/SMNaNNaN3.736796e+0900296F1
215.02016.04.0101.0101.0WAS20545.01.0MI20691.055.02.01.020160401NaNNaNTONaNM1961.009302016MNaNOS6.666432e+0893B2
316.02016.04.0101.0101.0NYC20545.01.0MA20567.028.02.01.020160401NaNNaNOONaNM1988.009302016NaNNaNAA9.246846e+1000199B2
417.02016.04.0101.0101.0NYC20545.01.0MA20567.04.02.01.020160401NaNNaNOONaNM2012.009302016NaNNaNAA9.246846e+1000199B2
\n", "
" ], "text/plain": [ " cicid i94yr i94mon i94cit i94res i94port arrdate i94mode i94addr \\\n", "0 6.0 2016.0 4.0 692.0 692.0 XXX 20573.0 NaN NaN \n", "1 7.0 2016.0 4.0 254.0 276.0 ATL 20551.0 1.0 AL \n", "2 15.0 2016.0 4.0 101.0 101.0 WAS 20545.0 1.0 MI \n", "3 16.0 2016.0 4.0 101.0 101.0 NYC 20545.0 1.0 MA \n", "4 17.0 2016.0 4.0 101.0 101.0 NYC 20545.0 1.0 MA \n", "\n", " depdate i94bir i94visa count dtadfile visapost occup entdepa entdepd \\\n", "0 NaN 37.0 2.0 1.0 NaN NaN NaN T NaN \n", "1 NaN 25.0 3.0 1.0 20130811 SEO NaN G NaN \n", "2 20691.0 55.0 2.0 1.0 20160401 NaN NaN T O \n", "3 20567.0 28.0 2.0 1.0 20160401 NaN NaN O O \n", "4 20567.0 4.0 2.0 1.0 20160401 NaN NaN O O \n", "\n", " entdepu matflag biryear dtaddto gender insnum airline admnum \\\n", "0 U NaN 1979.0 10282016 NaN NaN NaN 1.897628e+09 \n", "1 Y NaN 1991.0 D/S M NaN NaN 3.736796e+09 \n", "2 NaN M 1961.0 09302016 M NaN OS 6.666432e+08 \n", "3 NaN M 1988.0 09302016 NaN NaN AA 9.246846e+10 \n", "4 NaN M 2012.0 09302016 NaN NaN AA 9.246846e+10 \n", "\n", " fltno visatype \n", "0 NaN B2 \n", "1 00296 F1 \n", "2 93 B2 \n", "3 00199 B2 \n", "4 00199 B2 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.set_option('display.max_columns', None)\n", "immigration.head()" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### Data Dictionary:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "editable": true }, "outputs": [], "source": [ "with open('./I94_SAS_Labels_Descriptions.SAS') as f:\n", " f_content = f.read()\n", " f_content = f_content.replace('\\t', '')\n", "def code_mapper(file, idx):\n", " f_content2 = f_content[f_content.index(idx):]\n", " f_content2 = f_content2[:f_content2.index(';')].split('\\n')\n", " f_content2 = [i.replace(\"'\", \"\") for i in f_content2]\n", " dic = [i.split('=') for i in f_content2[1:]]\n", " dic = dict([i[0].strip(), i[1].strip()] for i in dic if len(i) == 2)\n", " return dic\n", "\n", "i94cit_res = code_mapper(f_content, \"i94cntyl\")\n", "i94port = code_mapper(f_content, \"i94prtl\")\n", "i94mode = code_mapper(f_content, \"i94model\")\n", "i94addr = code_mapper(f_content, \"i94addrl\")\n", "i94visa = {'1':'Business','2': 'Pleasure','3' : 'Student'}" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "editable": true, "toggleable": false, "ulab": { "buttons": { "ulab-button-toggle-3e93d7e7": { "style": "primary" } } } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
description
cicidID that uniquely identify one record in the da...
i94yrYear (YYYY)
i94monMonth (MM)
i94citBorn City number
i94resResident City number
i94portPort Short Code
arrdateArrival date
i94modeMode: ([1,2,3,9],['Air','Sea', 'Land', 'NA'])
i94addrArrival US States shortcodes
depdateDeparture date
i94birAge of respondent
i94visaVisa codes: ([1,2,3],['Business', 'Tourism', '...
countfor summary statistics propose
dtadfileDocument date YYYYMMDD
visapostDepartment where Visa was issued
occupOccupation that will be performed in U.S.
entdepaArrival flag
entdepdDeparture flag
entdepuUpdate flag
matflagMatch flag
biryearBirth year
dtaddtoDate of US admition MMDDYYYY
genderGender
insnumINS number
airlineAirline used to arrive in U.S.
admnumAdmission number (unique)
fltnoFlight number of Airline used to arrive in U.S.
visatypeClass of admission legally admitting the non-i...
\n", "
" ], "text/plain": [ " description\n", "cicid ID that uniquely identify one record in the da...\n", "i94yr Year (YYYY)\n", "i94mon Month (MM)\n", "i94cit Born City number\n", "i94res Resident City number\n", "i94port Port Short Code\n", "arrdate Arrival date\n", "i94mode Mode: ([1,2,3,9],['Air','Sea', 'Land', 'NA'])\n", "i94addr Arrival US States shortcodes\n", "depdate Departure date\n", "i94bir Age of respondent\n", "i94visa Visa codes: ([1,2,3],['Business', 'Tourism', '...\n", "count for summary statistics propose\n", "dtadfile Document date YYYYMMDD\n", "visapost Department where Visa was issued\n", "occup Occupation that will be performed in U.S.\n", "entdepa Arrival flag\n", "entdepd Departure flag\n", "entdepu Update flag\n", "matflag Match flag\n", "biryear Birth year\n", "dtaddto Date of US admition MMDDYYYY\n", "gender Gender\n", "insnum INS number\n", "airline Airline used to arrive in U.S.\n", "admnum Admission number (unique)\n", "fltno Flight number of Airline used to arrive in U.S.\n", "visatype Class of admission legally admitting the non-i..." ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "immigration_columns_description = [\n", " 'ID that uniquely identify one record in the dataset',\n", " 'Year (YYYY)',\n", " 'Month (MM)',\n", " 'Born City number',\n", " 'Resident City number',\n", " 'Port Short Code',\n", " 'Arrival date',\n", " \"Mode: ([1,2,3,9],['Air','Sea', 'Land', 'NA'])\",\n", " 'Arrival US States shortcodes',\n", " 'Departure date',\n", " 'Age of respondent',\n", " \"Visa codes: ([1,2,3],['Business', 'Tourism', 'Student'])\",\n", " 'for summary statistics propose',\n", " 'Document date YYYYMMDD',\n", " 'Department where Visa was issued',\n", " 'Occupation that will be performed in U.S.',\n", " 'Arrival flag',\n", " 'Departure flag',\n", " 'Update flag',\n", " 'Match flag',\n", " 'Birth year',\n", " 'Date of US admition MMDDYYYY',\n", " 'Gender',\n", " 'INS number',\n", " 'Airline used to arrive in U.S.',\n", " 'Admission number (unique)',\n", " 'Flight number of Airline used to arrive in U.S.',\n", " 'Class of admission legally admitting the non-immigrant to temporarily stay in U.S.'\n", "]\n", "\n", "immigration_dict = pd.DataFrame(immigration_columns_description, immigration.columns, columns=['description'])\n", "immigration_dict" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### World Temperature Data" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "editable": true }, "outputs": [], "source": [ "temperature_fname = '../../data2/GlobalLandTemperaturesByCity.csv'\n", "world_temperature = pd.read_csv(temperature_fname)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
dtAverageTemperatureAverageTemperatureUncertaintyCityCountryLatitudeLongitude
01743-11-016.0681.737ÅrhusDenmark57.05N10.33E
11743-12-01NaNNaNÅrhusDenmark57.05N10.33E
21744-01-01NaNNaNÅrhusDenmark57.05N10.33E
31744-02-01NaNNaNÅrhusDenmark57.05N10.33E
41744-03-01NaNNaNÅrhusDenmark57.05N10.33E
\n", "
" ], "text/plain": [ " dt AverageTemperature AverageTemperatureUncertainty City \\\n", "0 1743-11-01 6.068 1.737 Århus \n", "1 1743-12-01 NaN NaN Århus \n", "2 1744-01-01 NaN NaN Århus \n", "3 1744-02-01 NaN NaN Århus \n", "4 1744-03-01 NaN NaN Århus \n", "\n", " Country Latitude Longitude \n", "0 Denmark 57.05N 10.33E \n", "1 Denmark 57.05N 10.33E \n", "2 Denmark 57.05N 10.33E \n", "3 Denmark 57.05N 10.33E \n", "4 Denmark 57.05N 10.33E " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "world_temperature.head()" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### Data Dictionary:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
description
dtDate in format YYYY-MM-DD
AverageTemperatureAverage temperature of the city in a given date
AverageTemperatureUncertaintyAverage Temperature Uncertainty
CityCity Name
CountryCountry Name
LatitudeLatitude
LongitudeLongitude
\n", "
" ], "text/plain": [ " description\n", "dt Date in format YYYY-MM-DD\n", "AverageTemperature Average temperature of the city in a given date\n", "AverageTemperatureUncertainty Average Temperature Uncertainty\n", "City City Name\n", "Country Country Name\n", "Latitude Latitude\n", "Longitude Longitude" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "world_temperature_description = [\n", " 'Date in format YYYY-MM-DD',\n", " 'Average temperature of the city in a given date',\n", " 'Average Temperature Uncertainty',\n", " 'City Name',\n", " 'Country Name',\n", " 'Latitude',\n", " 'Longitude'\n", "]\n", "\n", "pd.DataFrame(world_temperature_description, world_temperature.columns, columns=['description'])\n" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### U.S. City Demographic Data:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "editable": true }, "outputs": [], "source": [ "us_cities_demographics = pd.read_csv(\"us-cities-demographics.csv\", sep=\";\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
CityStateMedian AgeMale PopulationFemale PopulationTotal PopulationNumber of VeteransForeign-bornAverage Household SizeState CodeRaceCount
0Silver SpringMaryland33.840601.041862.0824631562.030908.02.60MDHispanic or Latino25924
1QuincyMassachusetts41.044129.049500.0936294147.032935.02.39MAWhite58723
2HooverAlabama38.538040.046799.0848394819.08229.02.58ALAsian4759
3Rancho CucamongaCalifornia34.588127.087105.01752325821.033878.03.18CABlack or African-American24437
4NewarkNew Jersey34.6138040.0143873.02819135829.086253.02.73NJWhite76402
\n", "
" ], "text/plain": [ " City State Median Age Male Population \\\n", "0 Silver Spring Maryland 33.8 40601.0 \n", "1 Quincy Massachusetts 41.0 44129.0 \n", "2 Hoover Alabama 38.5 38040.0 \n", "3 Rancho Cucamonga California 34.5 88127.0 \n", "4 Newark New Jersey 34.6 138040.0 \n", "\n", " Female Population Total Population Number of Veterans Foreign-born \\\n", "0 41862.0 82463 1562.0 30908.0 \n", "1 49500.0 93629 4147.0 32935.0 \n", "2 46799.0 84839 4819.0 8229.0 \n", "3 87105.0 175232 5821.0 33878.0 \n", "4 143873.0 281913 5829.0 86253.0 \n", "\n", " Average Household Size State Code Race Count \n", "0 2.60 MD Hispanic or Latino 25924 \n", "1 2.39 MA White 58723 \n", "2 2.58 AL Asian 4759 \n", "3 3.18 CA Black or African-American 24437 \n", "4 2.73 NJ White 76402 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "us_cities_demographics.head()" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### Data Dictionary:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
description
CityUS City name
StateUS State name
Median AgeThe median of the age of the population
Male PopulationNumber of the male population
Female PopulationNumber of the female population
Total PopulationNumber of the total population
Number of VeteransNumber of veterans living in the city
Foreign-bornNumber of residents of the city that were not ...
Average Household SizeAverage size of the houses in the city
State CodeCode of the state of the city
RaceRace class
CountNumber of individual of each race
\n", "
" ], "text/plain": [ " description\n", "City US City name\n", "State US State name\n", "Median Age The median of the age of the population\n", "Male Population Number of the male population\n", "Female Population Number of the female population\n", "Total Population Number of the total population\n", "Number of Veterans Number of veterans living in the city\n", "Foreign-born Number of residents of the city that were not ...\n", "Average Household Size Average size of the houses in the city\n", "State Code Code of the state of the city\n", "Race Race class\n", "Count Number of individual of each race" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "us_cities_demographics_description = [\n", " 'US City name',\n", " 'US State name',\n", " 'The median of the age of the population',\n", " 'Number of the male population',\n", " 'Number of the female population',\n", " 'Number of the total population',\n", " 'Number of veterans living in the city',\n", " 'Number of residents of the city that were not born in the city',\n", " 'Average size of the houses in the city',\n", " 'Code of the state of the city',\n", " 'Race class',\n", " 'Number of individual of each race'\n", "]\n", "\n", "pd.DataFrame(us_cities_demographics_description, us_cities_demographics.columns, columns=['description'])" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### Airport Code Table" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "editable": true }, "outputs": [], "source": [ "airport = pd.read_csv(\"airport-codes_csv.csv\")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
identtypenameelevation_ftcontinentiso_countryiso_regionmunicipalitygps_codeiata_codelocal_codecoordinates
000AheliportTotal Rf Heliport11.0NaNUSUS-PABensalem00ANaN00A-74.93360137939453, 40.07080078125
100AAsmall_airportAero B Ranch Airport3435.0NaNUSUS-KSLeoti00AANaN00AA-101.473911, 38.704022
200AKsmall_airportLowell Field450.0NaNUSUS-AKAnchor Point00AKNaN00AK-151.695999146, 59.94919968
300ALsmall_airportEpps Airpark820.0NaNUSUS-ALHarvest00ALNaN00AL-86.77030181884766, 34.86479949951172
400ARclosedNewport Hospital & Clinic Heliport237.0NaNUSUS-ARNewportNaNNaNNaN-91.254898, 35.6087
\n", "
" ], "text/plain": [ " ident type name elevation_ft \\\n", "0 00A heliport Total Rf Heliport 11.0 \n", "1 00AA small_airport Aero B Ranch Airport 3435.0 \n", "2 00AK small_airport Lowell Field 450.0 \n", "3 00AL small_airport Epps Airpark 820.0 \n", "4 00AR closed Newport Hospital & Clinic Heliport 237.0 \n", "\n", " continent iso_country iso_region municipality gps_code iata_code \\\n", "0 NaN US US-PA Bensalem 00A NaN \n", "1 NaN US US-KS Leoti 00AA NaN \n", "2 NaN US US-AK Anchor Point 00AK NaN \n", "3 NaN US US-AL Harvest 00AL NaN \n", "4 NaN US US-AR Newport NaN NaN \n", "\n", " local_code coordinates \n", "0 00A -74.93360137939453, 40.07080078125 \n", "1 00AA -101.473911, 38.704022 \n", "2 00AK -151.695999146, 59.94919968 \n", "3 00AL -86.77030181884766, 34.86479949951172 \n", "4 NaN -91.254898, 35.6087 " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "airport.head()" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "##### Data Dictionary:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
description
identUnique identifier
typeType of the airport
nameAirport Name
elevation_ftAltitude of the airport
continentContinent
iso_countryISO code of the country of the airport
iso_regionISO code for the region of the airport
municipalityCity where the airport is located
gps_codeGPS code of the airport
iata_codeIATA code of the airport
local_codeLocal code of the airport
coordinatesGPS coordinates of the airport
\n", "
" ], "text/plain": [ " description\n", "ident Unique identifier\n", "type Type of the airport\n", "name Airport Name\n", "elevation_ft Altitude of the airport\n", "continent Continent\n", "iso_country ISO code of the country of the airport\n", "iso_region ISO code for the region of the airport\n", "municipality City where the airport is located\n", "gps_code GPS code of the airport\n", "iata_code IATA code of the airport\n", "local_code Local code of the airport\n", "coordinates GPS coordinates of the airport" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "airport_description = [\n", " 'Unique identifier',\n", " 'Type of the airport',\n", " 'Airport Name',\n", " 'Altitude of the airport',\n", " 'Continent',\n", " 'ISO code of the country of the airport',\n", " 'ISO code for the region of the airport',\n", " 'City where the airport is located',\n", " 'GPS code of the airport',\n", " 'IATA code of the airport',\n", " 'Local code of the airport',\n", " 'GPS coordinates of the airport'\n", "]\n", "pd.DataFrame(airport_description, airport.columns, columns=['description'])" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "### Step 2: Explore and Assess the Data\n", "#### Explore the Data \n", "Identify data quality issues, like missing values, duplicate data, etc.\n", "\n", "#### Cleaning Steps\n", "Document steps necessary to clean the data" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
cic_idyearmonthcity_codestate_codearrive_datedeparture_datemodevisa
06.02016.04.0XXXNaN20573.0NaNNaN2.0
17.02016.04.0ATLAL20551.0NaN1.03.0
215.02016.04.0WASMI20545.020691.01.02.0
316.02016.04.0NYCMA20545.020567.01.02.0
417.02016.04.0NYCMA20545.020567.01.02.0
\n", "
" ], "text/plain": [ " cic_id year month city_code state_code arrive_date departure_date \\\n", "0 6.0 2016.0 4.0 XXX NaN 20573.0 NaN \n", "1 7.0 2016.0 4.0 ATL AL 20551.0 NaN \n", "2 15.0 2016.0 4.0 WAS MI 20545.0 20691.0 \n", "3 16.0 2016.0 4.0 NYC MA 20545.0 20567.0 \n", "4 17.0 2016.0 4.0 NYC MA 20545.0 20567.0 \n", "\n", " mode visa \n", "0 NaN 2.0 \n", "1 1.0 3.0 \n", "2 1.0 2.0 \n", "3 1.0 2.0 \n", "4 1.0 2.0 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Performing cleaning tasks here\n", "\n", "f_immigration = immigration[['cicid', 'i94yr', 'i94mon', 'i94port', 'i94addr', 'arrdate', 'depdate', 'i94mode', 'i94visa']]\n", "f_immigration.columns = ['cic_id', 'year', 'month', 'city_code', 'state_code', 'arrive_date', 'departure_date', 'mode', 'visa']\n", "f_immigration.head()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
cic_idcitizen_countryresidence_countrybirth_yeargenderins_num
06.0692.0692.01979.0NaNNaN
17.0254.0276.01991.0MNaN
215.0101.0101.01961.0MNaN
316.0101.0101.01988.0NaNNaN
417.0101.0101.02012.0NaNNaN
\n", "
" ], "text/plain": [ " cic_id citizen_country residence_country birth_year gender ins_num\n", "0 6.0 692.0 692.0 1979.0 NaN NaN\n", "1 7.0 254.0 276.0 1991.0 M NaN\n", "2 15.0 101.0 101.0 1961.0 M NaN\n", "3 16.0 101.0 101.0 1988.0 NaN NaN\n", "4 17.0 101.0 101.0 2012.0 NaN NaN" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_citzen = immigration[['cicid', 'i94cit', 'i94res', 'biryear', 'gender', 'insnum']]\n", "d_citzen.columns = [['cic_id', 'citizen_country', 'residence_country', 'birth_year', 'gender', 'ins_num']]\n", "d_citzen.head(5)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
cic_idairlineadmin_numflight_numbervisa_type
06.0NaN1.897628e+09NaNB2
17.0NaN3.736796e+0900296F1
215.0OS6.666432e+0893B2
316.0AA9.246846e+1000199B2
417.0AA9.246846e+1000199B2
\n", "
" ], "text/plain": [ " cic_id airline admin_num flight_number visa_type\n", "0 6.0 NaN 1.897628e+09 NaN B2\n", "1 7.0 NaN 3.736796e+09 00296 F1\n", "2 15.0 OS 6.666432e+08 93 B2\n", "3 16.0 AA 9.246846e+10 00199 B2\n", "4 17.0 AA 9.246846e+10 00199 B2" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_airline = immigration[['cicid', 'airline', 'admnum', 'fltno', 'visatype']]\n", "d_airline.columns = ['cic_id', 'airline', 'admin_num', 'flight_number', 'visa_type']\n", "d_airline.head(5)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
dtavg_tempavg_temp_uncertntycity
475551820-01-012.1013.217Abilene
475561820-02-016.9262.853Abilene
475571820-03-0110.7672.395Abilene
475581820-04-0117.9892.202Abilene
475591820-05-0121.8092.036Abilene
\n", "
" ], "text/plain": [ " dt avg_temp avg_temp_uncertnty city\n", "47555 1820-01-01 2.101 3.217 Abilene\n", "47556 1820-02-01 6.926 2.853 Abilene\n", "47557 1820-03-01 10.767 2.395 Abilene\n", "47558 1820-04-01 17.989 2.202 Abilene\n", "47559 1820-05-01 21.809 2.036 Abilene" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_temperature = world_temperature[world_temperature.Country == 'United States']\n", "d_temperature = d_temperature[['dt', 'AverageTemperature', 'AverageTemperatureUncertainty', 'City']]\n", "d_temperature.columns = ['dt', 'avg_temp', 'avg_temp_uncertnty', 'city']\n", "d_temperature.head(5)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "editable": true }, "outputs": [], "source": [ "d_temperature['dt'] = pd.to_datetime(d_temperature['dt'])\n", "d_temperature['year'] = d_temperature['dt'].dt.year\n", "d_temperature['month'] = d_temperature['dt'].dt.month" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
dtavg_tempavg_temp_uncertntycityyearmonth
475551820-01-012.1013.217Abilene18201
475561820-02-016.9262.853Abilene18202
475571820-03-0110.7672.395Abilene18203
475581820-04-0117.9892.202Abilene18204
475591820-05-0121.8092.036Abilene18205
\n", "
" ], "text/plain": [ " dt avg_temp avg_temp_uncertnty city year month\n", "47555 1820-01-01 2.101 3.217 Abilene 1820 1\n", "47556 1820-02-01 6.926 2.853 Abilene 1820 2\n", "47557 1820-03-01 10.767 2.395 Abilene 1820 3\n", "47558 1820-04-01 17.989 2.202 Abilene 1820 4\n", "47559 1820-05-01 21.809 2.036 Abilene 1820 5" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_temperature.head()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
citystatemale_popfemale_popnum_vetaransforeign_bornrace
0Silver SpringMaryland40601.041862.01562.030908.0Hispanic or Latino
1QuincyMassachusetts44129.049500.04147.032935.0White
2HooverAlabama38040.046799.04819.08229.0Asian
3Rancho CucamongaCalifornia88127.087105.05821.033878.0Black or African-American
4NewarkNew Jersey138040.0143873.05829.086253.0White
\n", "
" ], "text/plain": [ " city state male_pop female_pop num_vetarans \\\n", "0 Silver Spring Maryland 40601.0 41862.0 1562.0 \n", "1 Quincy Massachusetts 44129.0 49500.0 4147.0 \n", "2 Hoover Alabama 38040.0 46799.0 4819.0 \n", "3 Rancho Cucamonga California 88127.0 87105.0 5821.0 \n", "4 Newark New Jersey 138040.0 143873.0 5829.0 \n", "\n", " foreign_born race \n", "0 30908.0 Hispanic or Latino \n", "1 32935.0 White \n", "2 8229.0 Asian \n", "3 33878.0 Black or African-American \n", "4 86253.0 White " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_population = us_cities_demographics[['City', 'State', 'Male Population', 'Female Population', 'Number of Veterans', 'Foreign-born', 'Race']]\n", "d_population.columns = ['city', 'state', 'male_pop', 'female_pop', 'num_vetarans', 'foreign_born', 'race']\n", "d_population.head(5)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
citystatemedian_ageavg_household_size
0Silver SpringMaryland33.82.60
1QuincyMassachusetts41.02.39
2HooverAlabama38.52.58
3Rancho CucamongaCalifornia34.53.18
4NewarkNew Jersey34.62.73
\n", "
" ], "text/plain": [ " city state median_age avg_household_size\n", "0 Silver Spring Maryland 33.8 2.60\n", "1 Quincy Massachusetts 41.0 2.39\n", "2 Hoover Alabama 38.5 2.58\n", "3 Rancho Cucamonga California 34.5 3.18\n", "4 Newark New Jersey 34.6 2.73" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_city_statistics = us_cities_demographics[['City', 'State', 'Median Age', 'Average Household Size']]\n", "d_city_statistics.columns = ['city', 'state', 'median_age', 'avg_household_size']\n", "d_city_statistics.head(5)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "editable": true }, "outputs": [], "source": [ "with open(\"I94_SAS_Labels_Descriptions.SAS\") as f:\n", " contents = f.readlines()" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "editable": true }, "outputs": [], "source": [ "country_code = {}\n", "for countries in contents[10:245]:\n", " pair = countries.split('=')\n", " code, country = pair[0].strip(), pair[1].strip().strip(\"'\")\n", " country_code[code] = country" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
codecountry
0236AFGHANISTAN
1101ALBANIA
2316ALGERIA
3102ANDORRA
4324ANGOLA
\n", "
" ], "text/plain": [ " code country\n", "0 236 AFGHANISTAN\n", "1 101 ALBANIA\n", "2 316 ALGERIA\n", "3 102 ANDORRA\n", "4 324 ANGOLA" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_country_code = pd.DataFrame(list(country_code.items()), columns=['code', 'country'])\n", "df_country_code.head(5)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "editable": true }, "outputs": [], "source": [ "city_code = {}\n", "for cities in contents[302:962]:\n", " pair = cities.split('=')\n", " code, city = pair[0].strip(\"\\t\").strip().strip(\"'\"), pair[1].strip('\\t').strip().strip(\"''\")\n", " city_code[code] = city" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
codecity
0ALCALCAN, AK
1ANCANCHORAGE, AK
2BARBAKER AAF - BAKER ISLAND, AK
3DACDALTONS CACHE, AK
4PIZDEW STATION PT LAY DEW, AK
\n", "
" ], "text/plain": [ " code city\n", "0 ALC ALCAN, AK \n", "1 ANC ANCHORAGE, AK \n", "2 BAR BAKER AAF - BAKER ISLAND, AK\n", "3 DAC DALTONS CACHE, AK \n", "4 PIZ DEW STATION PT LAY DEW, AK" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_city_code = pd.DataFrame(list(city_code.items()), columns=['code', 'city'])\n", "df_city_code.head(5)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "editable": true }, "outputs": [], "source": [ "state_code = {}\n", "for states in contents[981:1036]:\n", " pair = states.split('=')\n", " code, state = pair[0].strip('\\t').strip(\"'\"), pair[1].strip().strip(\"'\")\n", " state_code[code] = state" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "editable": true }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
codestate
0ALALABAMA
1AKALASKA
2AZARIZONA
3ARARKANSAS
4CACALIFORNIA
\n", "
" ], "text/plain": [ " code state\n", "0 AL ALABAMA\n", "1 AK ALASKA\n", "2 AZ ARIZONA\n", "3 AR ARKANSAS\n", "4 CA CALIFORNIA" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_state_code = pd.DataFrame(list(state_code.items()), columns=['code', 'state'])\n", "df_state_code.head(5)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "editable": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", " \"\"\"Entry point for launching an IPython kernel.\n", "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", " \n" ] }, { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
citystatemedian_ageavg_household_size
0SILVER SPRINGMARYLAND33.82.60
1QUINCYMASSACHUSETTS41.02.39
2HOOVERALABAMA38.52.58
3RANCHO CUCAMONGACALIFORNIA34.53.18
4NEWARKNEW JERSEY34.62.73
\n", "
" ], "text/plain": [ " city state median_age avg_household_size\n", "0 SILVER SPRING MARYLAND 33.8 2.60\n", "1 QUINCY MASSACHUSETTS 41.0 2.39\n", "2 HOOVER ALABAMA 38.5 2.58\n", "3 RANCHO CUCAMONGA CALIFORNIA 34.5 3.18\n", "4 NEWARK NEW JERSEY 34.6 2.73" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "d_city_statistics['city'] = d_city_statistics['city'].str.upper()\n", "d_city_statistics['state'] = d_city_statistics['state'].str.upper()\n", "d_city_statistics.head(5)" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "### Step 3: Define the Data Model\n", "#### 3.1 Conceptual Data Model\n", "Map out the conceptual data model and explain why you chose that model\n", "\n" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "editable": true }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython import display\n", "display.Image(\"./data-model.png\")" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### 3.2 Mapping Out Data Pipelines\n", "List the steps necessary to pipeline the data into the chosen data model" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "**Please refer to [etl file](./etl.ipynb) to see in details.**" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "### Step 4: Run Pipelines to Model the Data \n", "#### 4.1 Create the data model\n", "Build the data pipelines to create the data model." ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "**Please refer to [etl file](./etl.ipynb) to see in details.**" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### 4.2 Data Quality Checks\n", "Explain the data quality checks you'll perform to ensure the pipeline ran as expected. These could include:\n", " * Integrity constraints on the relational database (e.g., unique key, data type, etc.)\n", " * Unit tests for the scripts to ensure they are doing the right thing\n", " * Source/Count checks to ensure completeness\n", " \n", "Run Quality Checks" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "**Please refer to [Quality-checks file](./Quality-checks.ipynb) to see in details.**" ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### 4.3 Data dictionary \n", "Create a data dictionary for your data model. For each field, provide a brief description of what the data is and where it came from. You can include the data dictionary in the notebook or in a separate file." ] }, { "cell_type": "markdown", "metadata": { "editable": true }, "source": [ "#### Step 5: Complete Project Write Up\n", "* Clearly state the rationale for the choice of tools and technologies for the project.\n", "* Propose how often the data should be updated and why.\n", "* Write a description of how you would approach the problem differently under the following scenarios:\n", " * The data was increased by 100x.\n", " * The data populates a dashboard that must be updated on a daily basis by 7am every day.\n", " * The database needed to be accessed by 100+ people." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "editable": true }, "outputs": [], "source": [] } ], "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": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 4 }