Load Data With Pandas

 

Pandas is one of the most popular data manipulation libraries in python, so in this post, let’s take a look at the most common ways to load data into a pandas dataframe.

Load CSV

First up, let’s try loading data from a csv.

Loading data from a csv is probably the most popular way of getting your data into pandas.

Pandas makes it easy for us with the read_csv command.

import pandas as pd

csv_path = "path_to_csv_file"

df = pd.read_csv(csv_path)

Load Excel

Another common file type for tabular data is excel. Let’s take a look at how to load an excel spreadsheet.

import pandas as pd

excel_path = "path_to_excel_file"

df = pd.read_excel(excel_path)

Load JSON

Json is commonly used in applications on the web. Most web api’s communicate via Json nowadays. Let’s take a look at how to get Json into our dataframe.

import pandas as pd

json_path = "path_to_json_file"

df = pd.read_json(json_path)

Load By SQL

Lastly, relational databases are super common in software. Using sqlalchemy, let’s take a look at how to query data from our database.

import pandas as pd
from sqlalchemy import create_engine

conn = create_engine('sqlite:///test.db')

df = pd.read_sql_query('SELECT * FROM table_name', conn)