Python psycopg2 insert NULL in some rows in postgresql table

Question

I have a Python dataframe with NULL value in some rows, while inserting to postgresql, some null in datetype column turns into 'NaT' string or 'NaN', I like it to be a real NULL , which is nothing in that cell.

sample dataframe before insert

import psycopg2
import pandas as pd
import numpy as np

conn=psycopg2.connect(dbname= 'myDB', host='amazonaws.com', 
port= '2222', user= 'mysuser', password= 'mypass')
cur = conn.cursor()

df= pd.DataFrame({ 'zipcode':[1,np.nan,22,88],'city':['A','h','B',np.nan]})


subset = df[['zipcode', 'city']]
data = [tuple(x) for x in subset.values]
records_list_template = ','.join(['%s'] * len(data)) 
insert_query = 'insert into public.MyTable (zipcode, city) values {}'.format(records_list_template)
cur.execute(insert_query, data)
conn.commit()

result in postgresql table

expected result below

klin · Accepted Answer · 2019-01-30 00:06:45Z

3

You can convert NaN to None in this way:

df= pd.DataFrame({
    'zipcode':[1,np.nan,22,88],
    'city':['A','h','B',np.nan],
    'date':['2019-01-01','2019-01-02',pd.NaT,pd.NaT]})

df['date'] = [d.strftime('%Y-%m-%d') if not pd.isnull(d) else None for d in df['date']]

subset = df.where((pd.notnull(df)), None)

See DataFrame.where

edited Jan 30, 2019 at 0:06

answered Jan 29, 2019 at 20:51

klin

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7 Comments

PyBoss Over a year ago

my bad, my actual table contains a datetype column which has some NaT, the df.where((pd.notnull(df)), None) can't convert NaT

klin Over a year ago

Indeed, it does not work with NaT (I thought it should). I added a conversion from NaT to None in a specific column, see the updated answer.

PyBoss Over a year ago

by the way, do you know how to speed up the process if I have 1 millions rows to insert? Bulk insert?

klin Over a year ago

Do you have the data in a file?

PyBoss Over a year ago

it's in pandas dataframe, I can save it as a csv.

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Ben Sharkey · Accepted Answer · 2019-07-22 02:12:10Z

2

Convert all instances of NaN in the dataframe by replacing with None, like this:

df = df.replace({pd.np.nan: None})

answered Jul 22, 2019 at 2:12

Ben Sharkey

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1 Comment

bucky Over a year ago

if you do this, than there will be 'None' in the postgres db. the OP wants to have [null] in the db

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