Overview website: http://ilrdss.isws.illinois.edu/fox/
To acquire the CSV file from MS access we first converted the .mdb database into SQLite. Once we had access to the .sqlite3 file we created a python script to access it, execute SQL statements, and generate a CSV file from the resulting table.
- Data location: gltg-source-data/Fox River Watershed Database
- CSV for latest sqlite3 file: selected_final_foxdb_20171116.csv
- Lastest MS access db: FoxDB_20171116.mdb
- Converted sqlite3 file: foxdb_20171116.sqlite3 (please use this one)
- Database design document:
Code Block |
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SELECT tblsample.station_id,
tblstation_information.latitude,
tblstation_information.longitude,
tblstation_information.place_name_description,
tblsample.sample_code,
tblsample.idloc,
tblparameter_codes.full_name,
tblparameter_codes.short_name,
tblsample.start_date,
tblresults.result_value,
tblparameter_group.parameter_group
FROM (((( (tblresults
INNER JOIN tblsample
ON ( tblresults.sample_code = tblsample.sample_code )
AND ( tblresults.idloc = tblsample.idloc ))
INNER JOIN tblparameter_codes
ON tblresults.parameter_code =
tblparameter_codes.parameter_code)
INNER JOIN tblqappgroups
ON tblparameter_codes.parameter_code =
tblqappgroups.parameter_code)
INNER JOIN tblqapp_group_codes
ON tblqappgroups.qappcode = tblqapp_group_codes.qappcode)
INNER JOIN tblparameter_group
ON tblqapp_group_codes.parameter_group =
tblparameter_group.parameter_group)
LEFT JOIN tblstation_information
ON tblstation_information.station_id = tblsample.station_id
WHERE (( ( tblparameter_group.parameter_group ) = 9
OR ( tblparameter_group.parameter_group ) = 10 )) |
Code Block |
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""" Access a sqlite3 file,
executes a SQL statement, and
generates a CSV file for parsing
Variables
----------
data_loc : str
The location of the database (for example, ./foxdb/foxdb_20171116.sqlite3)
query : str
The SQL statement
"""
import sqlite3
import pandas as pd
data_loc = ""
query = ""
conn = sqlite3.connect(data_loc)
df = pd.read_sql_query(query, conn)
df['Start_Date'] = pd.to_datetime(df['Start_Date'], errors='coerce') #use this to format date and time to only date
df.to_csv("output.csv", encoding='utf-8', index=False, date_format='%Y-%m-%d')
conn.close()
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Resources:
- Presentation at Nutrient Monitoring Council that explains what kinds of query Jong Lee did to extract the data from the database.
View file |
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name | NMC-Fox-River-Data.pptx |
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height | 250 |
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- Python sqlite3 module
- Python Data Analysis Library