From bd0b175d9b800dfd96feb2fdfe74bbb038765600 Mon Sep 17 00:00:00 2001
From: Jamie Ballingall <jamie@quadrics.xyz>
Date: Mon, 2 Sep 2024 12:20:24 -0400
Subject: [PATCH] First working code

---
 README.md | 29 ++++++++++++++++++++++++++++-
 main.py   | 10 ++++++++++
 2 files changed, 38 insertions(+), 1 deletion(-)
 create mode 100644 main.py

diff --git a/README.md b/README.md
index d8d7f80..85d88d7 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,28 @@
-"# nba_api" 
+# NBA API demo
+
+A proof-of-concept / demo for the `nba_api`
+
+# To create the environment from scratch
+conda create -n nba python=3.12
+conda activate nba
+conda install pandas
+pip install nba_api
+
+Then run
+```
+python main.py
+```
+
+Expect to see a large printout of a dictionary object beginning:
+```
+PLAYER_ID SEASON_ID LEAGUE_ID     TEAM_ID TEAM_ABBREVIATION  PLAYER_AGE  GP  ...   REB  AST  STL  BLK  TOV   PF   PTS
+0     203999   2015-16        00  1610612743               DEN        21.0  80  ...   560  189   79   50  104  208   796
+1     203999   2016-17        00  1610612743               DEN        22.0  73  ...   718  359   61   55  171  214  1221
+2     203999   2017-18        00  1610612743               DEN        23.0  75  ...   803  458   90   61  210  212  1385
+```
+
+We are using the API library:
+https://github.com/swar/nba_api
+
+There may be additional data available at through other libraries. See:
+https://medium.com/@cristianvaldez85/nba-data-using-python-82ebc0e19398
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..f69a7f9
--- /dev/null
+++ b/main.py
@@ -0,0 +1,10 @@
+from nba_api.stats.endpoints import playercareerstats
+
+# Nikola Jokić
+career = playercareerstats.PlayerCareerStats(player_id='203999')
+
+# pandas data frames (optional: pip install pandas)
+print(career.get_data_frames()[0])
+
+# dictionary
+# print(career.get_dict())