Introduction¶
Using this Python notebook you will:
- Understand 3 Chicago datasets
- Load the 3 datasets into 3 tables in a Db2 database
- Execute SQL queries to answer assignment questions
Understand the datasets¶
To complete the assignment problems in this notebook you will be using three datasets that are available on the city of Chicago's Data Portal:
1. Socioeconomic Indicators in Chicago¶
This dataset contains a selection of six socioeconomic indicators of public health significance and a “hardship index,” for each Chicago community area, for the years 2008 – 2012.
For this assignment you will use a snapshot of this dataset which can be downloaded from: https://ibm.box.com/shared/static/05c3415cbfbtfnr2fx4atenb2sd361ze.csv
A detailed description of this dataset and the original dataset can be obtained from the Chicago Data Portal at: https://data.cityofchicago.org/Health-Human-Services/Census-Data-Selected-socioeconomic-indicators-in-C/kn9c-c2s2
2. Chicago Public Schools¶
This dataset shows all school level performance data used to create CPS School Report Cards for the 2011-2012 school year. This dataset is provided by the city of Chicago's Data Portal.
For this assignment you will use a snapshot of this dataset which can be downloaded from: https://ibm.box.com/shared/static/f9gjvj1gjmxxzycdhplzt01qtz0s7ew7.csv
A detailed description of this dataset and the original dataset can be obtained from the Chicago Data Portal at: https://data.cityofchicago.org/Education/Chicago-Public-Schools-Progress-Report-Cards-2011-/9xs2-f89t
3. Chicago Crime Data¶
This dataset reflects reported incidents of crime (with the exception of murders where data exists for each victim) that occurred in the City of Chicago from 2001 to present, minus the most recent seven days.
This dataset is quite large - over 1.5GB in size with over 6.5 million rows. For the purposes of this assignment we will use a much smaller sample of this dataset which can be downloaded from: https://ibm.box.com/shared/static/svflyugsr9zbqy5bmowgswqemfpm1x7f.csv
A detailed description of this dataset and the original dataset can be obtained from the Chicago Data Portal at: https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-present/ijzp-q8t2
Download the datasets¶
In many cases the dataset to be analyzed is available as a .CSV (comma separated values) file, perhaps on the internet. Click on the links below to download and save the datasets (.CSV files):
- CENSUS_DATA: https://ibm.box.com/shared/static/05c3415cbfbtfnr2fx4atenb2sd361ze.csv
- CHICAGO_PUBLIC_SCHOOLS https://ibm.box.com/shared/static/f9gjvj1gjmxxzycdhplzt01qtz0s7ew7.csv
- CHICAGO_CRIME_DATA: https://ibm.box.com/shared/static/svflyugsr9zbqy5bmowgswqemfpm1x7f.csv
NOTE: Ensure you have downloaded the datasets using the links above instead of directly from the Chicago Data Portal. The versions linked here are subsets of the original datasets and have some of the column names modified to be more database friendly which will make it easier to complete this assignment.
Store the datasets in database tables¶
To analyze the data using SQL, it first needs to be stored in the database.
While it is easier to read the dataset into a Pandas dataframe and then PERSIST it into the database as we saw in Week 3 Lab 3, it results in mapping to default datatypes which may not be optimal for SQL querying. For example a long textual field may map to a CLOB instead of a VARCHAR.
Therefore, it is highly recommended to manually load the table using the database console LOAD tool, as indicated in Week 2 Lab 1 Part II. The only difference with that lab is that in Step 5 of the instructions you will need to click on create "(+) New Table" and specify the name of the table you want to create and then click "Next".
Now open the Db2 console, open the LOAD tool, Select / Drag the .CSV file for the first dataset, Next create a New Table, and then follow the steps on-screen instructions to load the data. Name the new tables as folows:¶
- CENSUS_DATA
- CHICAGO_PUBLIC_SCHOOLS
- CHICAGO_CRIME_DATA
Connect to the database¶
Let us first load the SQL extension and establish a connection with the database
%load_ext sql
In the next cell enter your db2 connection string. Recall you created Service Credentials for your Db2 instance in first lab in Week 3. From the uri field of your Db2 service credentials copy everything after db2:// (except the double quote at the end) and paste it in the cell below after ibm_db_sa://
dsn_driver = "{IBM DB2 ODBC DRIVER}"
dsn_database = "BLUDB" # e.g. "BLUDB"
dsn_port = "50000" # e.g. "50000"
dsn_protocol = "TCPIP" # i.e. "TCPIP"
%sql ibm_db_sa://rjz07540:xwc76jpv64jfwb%40v@dashdb-txn-sbox-yp-dal09-04.services.dal.bluemix.net:50000/BLUDB
# Rows in Crime table
%sql select count(*) from CHICAGO_CRIME_DATA;
%sql select * from CHICAGO_CRIME_DATA fetch first 10 rows only;
%sql select count(ARREST) from CHICAGO_CRIME_DATA WHERE ARREST=TRUE;
%sql select DISTINCT(PRIMARY_TYPE) from CHICAGO_CRIME_DATA WHERE LOCATION_DESCRIPTION ='GAS STATION';
Hint: Which column lists types of crimes e.g. THEFT?
%sql select COMMUNITY_AREA_NAME from CENSUS_DATA WHERE COMMUNITY_AREA_NAME LIKE 'B%';
%sql select S.NAME_OF_SCHOOL,C.COMMUNITY_AREA_NUMBER,C.COMMUNITY_AREA_NAME,S.healthy_school_certified from CENSUS_DATA as C \
LEFT OUTER JOIN CHICAGO_PUBLIC_SCHOOLS as S \
on UPPER(C.COMMUNITY_AREA_NAME) = UPPER(S.community_area_name) \
where C.COMMUNITY_AREA_NUMBER between 10 and 15 AND \
S.healthy_school_certified = 'Yes';
%sql select AVG(safety_score) as AVERAGE_SCRORE from CHICAGO_PUBLIC_SCHOOLS;
%sql select COMMUNITY_AREA_NAME,AVG(COLLEGE_ENROLLMENT) as COLLEGE_ENROLLMENT_AVG \
from CHICAGO_PUBLIC_SCHOOLS GROUP BY COMMUNITY_AREA_NAME order by COLLEGE_ENROLLMENT_AVG desc LIMIT 5;
%sql select COMMUNITY_AREA_NAME,SAFETY_SCORE from CHICAGO_PUBLIC_SCHOOLS \
WHERE SAFETY_SCORE = (SELECT MIN(SAFETY_SCORE) FROM CHICAGO_PUBLIC_SCHOOLS);
%sql select COMMUNITY_AREA_NAME,per_capita_income \
from CENSUS_DATA \
where community_area_number = (select community_area_number from CHICAGO_PUBLIC_SCHOOLS where safety_score = 1);
Copyright © 2018 cognitiveclass.ai. This notebook and its source code are released under the terms of the MIT License.