Difference between revisions of "2015 UK General Election using SQL Server"
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The first line of the CSV file contains the column headings (ons_id,ons_region_id,constituency_name,county_name,region_name,country_name,constituency_type,party_name,party_abbreviation,firstname,surname,gender,sitting_mp,former_mp,votes,share,change). We create a table with a column for each of these: | The first line of the CSV file contains the column headings (ons_id,ons_region_id,constituency_name,county_name,region_name,country_name,constituency_type,party_name,party_abbreviation,firstname,surname,gender,sitting_mp,former_mp,votes,share,change). We create a table with a column for each of these: | ||
sqlcmd -S .\sqlexpress -E | sqlcmd -S .\sqlexpress -E | ||
+ | We do not know the size of each column yet, too small and the import statement will give errors or warnings. It is best to be generous - memory is cheap. | ||
+ | |||
The create table statement could be: | The create table statement could be: | ||
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CREATE TABLE ge( | CREATE TABLE ge( | ||
ons_id VARCHAR(10), | ons_id VARCHAR(10), | ||
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PRIMARY KEY(ons_id,firstname,surname) | PRIMARY KEY(ons_id,firstname,surname) | ||
) | ) | ||
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==Attempt import the csv file into your flat table== | ==Attempt import the csv file into your flat table== |
Revision as of 07:40, 5 July 2017
This tutorial assumes you have access to powershell and sqlcmd or Microsoft SQL Server Management Studio
Contents
Get to the powershell prompt and download the csv
Invoke-WebRequest http://researchbriefings.files.parliament.uk/documents/CBP-7979/hocl-ge2017-results-full.csv -OutFile ge2017.csv
Go into sqlcmd or SSMS and create a table for the results
Here you create a single flat table that can store all of the unnormalised data.
The first line of the CSV file contains the column headings (ons_id,ons_region_id,constituency_name,county_name,region_name,country_name,constituency_type,party_name,party_abbreviation,firstname,surname,gender,sitting_mp,former_mp,votes,share,change). We create a table with a column for each of these:
sqlcmd -S .\sqlexpress -E
We do not know the size of each column yet, too small and the import statement will give errors or warnings. It is best to be generous - memory is cheap.
The create table statement could be:
CREATE TABLE ge( ons_id VARCHAR(10), ons_region_id VARCHAR(10), constituency_name VARCHAR(50), county_name VARCHAR(50), region_name VARCHAR(50), country_name VARCHAR(50), constituency_type VARCHAR(10), party_name VARCHAR(50), party_abbreviation VARCHAR(50), firstname VARCHAR(50), surname VARCHAR(50), gender VARCHAR(6), sitting_mp VARCHAR(3), former_mp VARCHAR(3), votes INT, share FLOAT, change VARCHAR(20), PRIMARY KEY(ons_id,firstname,surname) )
Attempt import the csv file into your flat table
You can import the data using this line (from SQLCMD or SQL Server Management Studio)
BULK INSERT ge FROM 'C:\db\ge2015.csv' WITH (FIELDTERMINATOR=',', ROWTERMINATOR='\n', FIRSTROW=2) GO
- Each line is ended with carriage return \n
- The first row contains column headings not data so we start at row 2
You will most likely get error messages like this:
Msg 4863, Level 16, State 1, Server ME1C039-130368\SQLEXPRESS, Line 3 Bulk load data conversion error (truncation) for row 105, column 13 (sitting_mp). Msg 4863, Level 16, State 1, Server ME1C039-130368\SQLEXPRESS, Line 3 Bulk load data conversion error (truncation) for row 106, column 12 (gender). Msg 4863, Level 16, State 1, Server ME1C039-130368\SQLEXPRESS, Line 3 Bulk load data conversion error (truncation) for row 107, column 13 (sitting_mp). ...
Unfortunately BULK INSERT cannot deal with the CSV format so we need to preprocess the file. Some solutions:
- Use Excel - you can load CSV and save as TXT
- Use regular expressions: convert CSV to TXT
- Use python
- Find a converter online
With the conversion complete you can import the data - you will have too use the full path name and you may have permissions problems
BULK INSERT ge FROM 'c:\path\ge2017.txt' WITH (FIRSTROW=2)
Run some queries
Now let's look at some data. How many female candidates were there?
select count(1) from ge where gender='female';
Who stood in Edinburgh South?
select surname,votes from ge where constituency_name='Edinburgh South';
You can now move to the next stage: 2015 UK General Election Normalising Data