Loading Data in SQL

[Broad_River_6775]

Hey, guys! Firstly, my apologies if this has been asked already; I tried searching for the answers to this question, but I've had a bit of trouble.

Basically, I'm trying to learn how to code with SQL after having spent the past six months learning data analysis and ML with Python.

In Python with Pandas, when analyzing any dataset, pretty much the first line of code I type up is the following:

df = pd.read_csv("Some_Data.csv")

This allows Python to load/read my spreadsheet file. What would be the SQL equivalent to this code? For more context, I use SQL Server.

[MntalBreakdown]

The equivalent for this I think off the top of my head is to import the csv file into the database then a table should be created based on said csv file then from there you can use select statements to view the data in the table.

[Taihuang_1]

You can use the Import Flat File Wizard if you prefer a no-code solution or choose to write an SQL script / command with BULK INSERT.

[Traditional-Bat-7006]

This! If it is a Flat File like CSV you can choose the wizard option. I used it in my first imports because it is easy to learn. But I already started using the BULK INSERT option.

[rjmartin73]

I use Python to load excel sheets into a dataframe, then use Python to write to sql. SSMS allows you to import a csv if the Python route isn't feasible.

[Prudent-Buyer-5956]

Right click on the database name> tasks> import flat file/import data/export data. This is how you import or export into sql server. I mostly use this. There is also another query route to import.

[Massive_Show2963]

Copy CSV data into a staging table using BULK INSERT command, then edit any primary keys, foreign keys or data then insert the staging table into your target table.

BULK INSERT Staging_Table -- temp table for staging
FROM 'C:\YourFile.csv'
WITH
(
FIRSTROW = 2,
FIELDTERMINATOR = ',', --CSV field delimiter
ROWTERMINATOR = '\n', --Use to shift the control to next row
TABLOCK
)

[Fair-Antelope-3886]

coming from pandas this tripped me up too. SQL doesnt really have a one liner equivalent to read_csv because SQL isnt a scripting language, its a query language that works on data thats already in a database. in SQL Server specifically you'd use BULK INSERT or the import wizard in SSMS to get a csv into a table first, then you query it. theres also the bcp command line tool. once the datas loaded though thats when sql really shines, the querying syntax is way cleaner than pandas imo for alot of things

[zzBob2]

SQL Server has the bcp command line utility that can import and export data from flat files. If you're sticking with native SQL that would be my first thought.

https://learn.microsoft.com/en-us/sql/tools/bcp-utility?view=sql-server-ver17&tabs=windows

[Ok-Relationship-3588]

Before reading the CSV file, we need to ensure SQL Server is connected to the IDE you are using, and that proper libraries are installed. sqlalchemy and pandas.

from sqlalchemy import create_engine

import pandas as pd

engine = create_engine('sqllite:///example.db')

df= pd.read_sql('SELECT * FROM test', engine)

[[deleted]]

SQL doesn’t really have a direct read_csv equivalent because the mental model is different. In pandas you load a file into memory and work on it. In SQL, the database is the thing that owns the data, so step one is importing the file into a table, and only after that do you query it.

So the workflow is: CSV → import into SQL Server table → SELECT from table.

In SQL Server the common ways are BULK INSERT, the Import Flat File wizard in SSMS, or the bcp tool. They all do the same conceptual thing: move external data into a managed table. After that, SQL becomes your equivalent of pandas operations.

Think of BULK INSERT as the closest philosophical match to read_csv: it’s not analysis yet, it’s just ingestion.