diff --git a/docs/pykx-under-q/upgrade.md b/docs/pykx-under-q/upgrade.md
index edc3ac4..388aee0 100644
--- a/docs/pykx-under-q/upgrade.md
+++ b/docs/pykx-under-q/upgrade.md
@@ -79,7 +79,7 @@ When generating workloads that integrate Python and q code, PyKX under q provide
 
 ### 1. Flexibility in supported data formats and conversions
 
-When using EmbedPy to convert data between q and Python, there’s a fundamental limitation related to supported data formats. Specifically, when passed to Python functions, q objects use the analogous Python/NumPy representation. This means that if an embedPy user requires data in a Pandas/PyArrow format, they need to convert it manually.
+When using EmbedPy to convert data between q and Python, there's a fundamental limitation related to supported data formats. Specifically, when passed to Python functions, q objects use the analogous Python/NumPy representation. This means that if an embedPy user requires data in a Pandas/PyArrow format, they need to convert it manually.
 
 As PyKX supports Python, NumPy, Pandas, and PyArrow data formats, it improves the workflow coverage and flexibility. For instance, PyKX by default converts q tables to Pandas DataFrames when passed to a Python function as follows: