Django Table - loading data table, accessing values
My background is 100% in Excel VBA. But I'm working on building some of my first web applications in Django framework. Please pardon me if this question is ridiculous.
I have a giant table (5000 rows x 7 columns) in a CSV file. I would like to somehow load this table into the Django framework -- and access the values in the table.
If the table were smaller, I could create a new model, then load the CSV into the model. But instinctively, it feels wrong to create a model with thousands of fields. Is there another way to load the table into Django framework, and reference the values via something like a vlookup function?
Thank you for any assistance!
django
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
add a comment |
My background is 100% in Excel VBA. But I'm working on building some of my first web applications in Django framework. Please pardon me if this question is ridiculous.
I have a giant table (5000 rows x 7 columns) in a CSV file. I would like to somehow load this table into the Django framework -- and access the values in the table.
If the table were smaller, I could create a new model, then load the CSV into the model. But instinctively, it feels wrong to create a model with thousands of fields. Is there another way to load the table into Django framework, and reference the values via something like a vlookup function?
Thank you for any assistance!
django
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06
add a comment |
My background is 100% in Excel VBA. But I'm working on building some of my first web applications in Django framework. Please pardon me if this question is ridiculous.
I have a giant table (5000 rows x 7 columns) in a CSV file. I would like to somehow load this table into the Django framework -- and access the values in the table.
If the table were smaller, I could create a new model, then load the CSV into the model. But instinctively, it feels wrong to create a model with thousands of fields. Is there another way to load the table into Django framework, and reference the values via something like a vlookup function?
Thank you for any assistance!
django
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
My background is 100% in Excel VBA. But I'm working on building some of my first web applications in Django framework. Please pardon me if this question is ridiculous.
I have a giant table (5000 rows x 7 columns) in a CSV file. I would like to somehow load this table into the Django framework -- and access the values in the table.
If the table were smaller, I could create a new model, then load the CSV into the model. But instinctively, it feels wrong to create a model with thousands of fields. Is there another way to load the table into Django framework, and reference the values via something like a vlookup function?
Thank you for any assistance!
django
django
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
asked Dec 28 '18 at 23:29
Mark1937Mark1937
12
12
7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06
add a comment |
7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06
7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06
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7 columns seems very reasonable for a model. On mobile but lookup some articles on introductions to dbs. A good first one is MySQL. Then read more on Django's orm. The answer is to make a model with fields for the seven columns. Then read the csv and insert the rows through Django's orm.
– dennmat
Dec 28 '18 at 23:42
Ty Dennmat. So the columns are geographic areas (like CITY, COUNTY, STATE). But all of the rows are unique. For example, row 100 could be "POPULATION_2000" -- then in the columns it would have City population as of 2000, County population as of 2000, etc. So if I wanted to access the "Population in 2000 for the City" --- how could I "lookup" to find the correct Row/Column intersection to get the value I want?
– Mark1937
Dec 29 '18 at 0:15
You could add a Year field to the model then when querying you could do stuff like. Population.objects.filter(year=2000, city='New York') and that would give you the row(s) that match New York and the Year 2000. It's hard to answer without having a clearer view of what the CSV structure really is.
– dennmat
Dec 29 '18 at 1:02
Thank you very much. I will explore the objects.FILTER technique, and see how that goes. It seems promising.
– Mark1937
Dec 30 '18 at 21:06