pd.read_sql_query() does not convert NULLs to NaN

A small, complete example of the issue

from sqlalchemy import create_engine
import pandas as pd

engine = create_engine('sqlite://')
conn = engine.connect()
conn.execute("create table test (a float)")
for _ in range(5):
    conn.execute("insert into test values (NULL)")

df = pd.read_sql_query("select * from test", engine, coerce_float=True)
print(df.a)

Expected Output

In pandas 0.18.1 this will result in a column of type object with None values, whereas I needed float(“nan”). The coerce_float=True option made no difference. This is most needed, when reading in a float column chunk-wise, since there may be sequences of NULLs.

(also http://stackoverflow.com/questions/30652457/adjust-pandas-read-sql-query-null-value-treatment/)

[annette987]

My actual query is more complicated than that and involves multiple tables. So I can’t just use pd.read_sql_table. What I am doing at the moment is just converting None to NaN in the dataframe: df.replace([None], np.nan, inplace=True)

[TomAugspurger]

Let’s actually reopen this, is it worth adding a coerce_null parameter to read_sql_query to handle cases like this?