Python and SQL : replacing the empty strings of a DataFrame by a “Null” value of SQL to insert the data in a database without error of format [duplicate]

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This question already has answers here:

Python/ SQL : replacing the empty strings of a DataFrame by a “Null” value to insert the data in a database (4 answers)

Python Pandas write to sql with NaN values (2 answers)

Replacing Pandas or Numpy Nan with a None to use with MysqlDB (7 answers)

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Let's say that I have this dataframe and this code to insert my data in the data base :

import pandas as pd
import pyodbc 


REFERENCE = ["GZF882348G", "SFGUZBJLNJU", "FTLNGZ242112", "DFBHGVGHG543", "H353464508749","H353464508749","H353464508749","H353464508749", "H353464508749", "H353464508749", "H353464508749"]
IBAN = ["FR57476", "FR57476", "FR57476", "FR57476", "FR57476", "FR57476", " FR57476", "FR57476", "FR57476", "FR57476", "FR57476"]
DATE = ["2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30", "2020-07-30"]
LIB = ["sdf", "dfsf", "dgsg", "dgfsg", "gsdg", "efsg", "efdg", "egsg", "gjtz", "wqeq", "hfgh"]
DEBIT = [289.2, 72.9, 709.23, 0, 97.3, 17.54, 40.32, 6.54, 1.74, '', 12401.04]
CREDIT = ['', '', '', '', '', '', '', '', '', 45, '']
BALANCE = [23.6,23.6,23.6,23.6,56.6,56,56,56,56,87,34]
B = ["CRDT", "CRDT", "CRDT", "CRDT", "DBIT", "DBIT", "DBIT", "DBIT", "DBIT", "CRDT", "DBIT"]
MONTANT = [-2819.2, -782.9, -709.23, 0, -9397.3, -1768.54, -1740.32, -676.54, -81.74, 16250, -12401.04]

df = pd.DataFrame({'Réference' : REFERENCE, 'IBAN' : IBAN, 'Date' : DATE, 'Libelle' : LIB, 'Débit' : DEBIT, 'Crédit' : CREDIT, 'Balance' : BALANCE, 'Balance DrCr':B, 'Montant' : MONTANT})

df[['Débit', 'Crédit', 'Balance', 'Montant']] = df[['Débit', 'Crédit', 'Balance', 'Montant']].apply(pd.to_numeric)

###### -------- Connection -----------------

server = '...'
database = '...'
username = '...' 
password = '...'
driver = '...'

connection = pyodbc.connect('DRIVER='+driver+';SERVER='+server+';PORT=1433;DATABASE='+database+';UID='+username+';PWD='+password)
cursor = connection.cursor()

##### ------- Insert into ----------------

sql_exe = "INSERT INTO dbo.tbl_data_xml (Réference,IBAN,Date,Libelle,Débit,Crédit,Balance,[Balance DrCr],Montant) VALUES (?,?,?,?,?,?,?,?,?)"

# CONVERT DATA TO LIST OF NUMPY ARRAYS
sql_data = df.to_numpy().tolist()

# EXECUTE ACTION QUERY
cursor.executemany(sql_exe, sql_data)
connection.commit()

I have a problem of format to insert this kind of data in my database. The columns "Débit", "Crédit", "Balance" and "Montant" are defined to get floats as data. However the data of these columns are not only integers, I have empty strings too and that is my issue. I know that I have to write a condition that replace a empty string by a "Null" value in the SQL format (the value null in SQL), however I do not know how to do that in python or in SQL. I am discovering/learning the SQL environment.

I do not know if I have to write a code in sql to replace by this value or if I can do it in the python function

Anyone has an idea ?

回答1:

Replace NaN with None

sql_data = df.replace({np.nan:None}).to_numpy().tolist()

来源：https://stackoverflow.com/questions/65080139/python-and-sql-replacing-the-empty-strings-of-a-dataframe-by-a-null-value-of

标签

python

sql-server

pandas

dataframe

pyodbc