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# Imports | |
import pandas as pd | |
from sqlalchemy import create_engine | |
# This CSV doesn't have a header so pass | |
# column names as an argument | |
columns = [ | |
"sepal_length", | |
"sepal_width", | |
"petal_length", | |
"petal_width", | |
"class" | |
] | |
# Load in the data | |
df = pd.read_csv( | |
"iris.csv", | |
names=columns | |
) | |
# Instantiate sqlachemy.create_engine object | |
engine = create_engine('postgresql://postgres:my_password@localhost:5432/iris') | |
# Save the data from dataframe to | |
# postgres table "iris_dataset" | |
df.to_sql( | |
'iris_dataset', | |
engine, | |
index=False # Not copying over the index | |
) |
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