diff --git a/analysis/analysis.py b/analysis/analysis.py
deleted file mode 100644
index 269f683..0000000
--- a/analysis/analysis.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import pandas as pd  # type: ignore
-import numpy as np  # type: ignore
-import matplotlib.pyplot as plt # type: ignore
-import seaborn as sns  # type: ignore
-import sqlalchemy as sql  # type: ignore
-
-# Create a database connection
-engine = sql.create_engine('postgresql://localhost:5432/robopoker')
-query =  """
-    WITH unique_abstraction AS (
-        SELECT DISTINCT abs
-        FROM turn_abs
-    ),
-    self_join_abstraction AS (
-        SELECT 
-            a.abs as abs1,
-            b.abs as abs2,
-            (a.abs # b.abs)::numeric as xor_result
-        FROM unique_abstraction a
-        CROSS JOIN unique_abstraction b
-        WHERE a.abs > b.abs
-    )
-    SELECT 
-        c.abs1,
-        c.abs2,
-        COALESCE(m.dst, 0) as dst
-    FROM self_join_abstraction c
-    LEFT JOIN turn_met m ON m.xab = c.xor_result::bigint
-"""
-
-
-# Read the query directly into a pandas DataFrame
-df = pd.read_sql(query, engine)
-
-df['x'] = df['abs1']
-df['y'] = df['abs2']
-
-# After loading the data
-abstractions_hex = sorted(set(df['x'].unique()) | set(df['y'].unique()))
-complete_index = pd.MultiIndex.from_product([abstractions_hex, abstractions_hex], names=['x', 'y'])
-complete_df = df.set_index(['x', 'y']).reindex(complete_index).reset_index()
-complete_df['dst'] = complete_df['dst'].fillna(0)  # Fill NaN with 0 or another appropriate value
-
-# Create a pivot table with the complete dataset
-pivot_df = complete_df.pivot(index='x', columns='y', values='dst')
-
-# Create a heatmap
-plt.figure(figsize=(24, 20))  # Increased figure size further
-sns.heatmap(pivot_df, cmap='YlOrRd', annot=False, square=True, xticklabels=True, yticklabels=True)
-plt.title('Turn Abstraction Distances')
-plt.xlabel('Abstraction 2')
-plt.ylabel('Abstraction 1')
-plt.xticks(rotation=90, fontsize=6)
-plt.yticks(rotation=0, fontsize=6)
-plt.tight_layout()
-plt.savefig(f'{int(pd.Timestamp.now().timestamp()) >> 8}.turn.metric.heatmap.png', dpi=300)
-plt.close()
-
-print("\nbasic statistics:")
-print(df['dst'].describe())
-
-print("\ntop 10 furthest pairs:")
-print(df.nlargest(10, 'dst')[['x', 'y', 'dst']])
-
-print("\ntop 10 closest pairs:") 
-print(df.nsmallest(10, 'dst')[['x', 'y', 'dst']])
-
-# Distribution of distances
-plt.figure(figsize=(10, 6))
-sns.histplot(df['dst'], kde=True)
-plt.title('distribution of turn abstraction distances')
-plt.xlabel('dst')
-plt.savefig(f'{int(pd.Timestamp.now().timestamp()) >> 8}.turn.metric.distribution.png')
-plt.close()
-
-print("Shape of pivot_df:", pivot_df.shape)
-print("Number of non-zero entries:", (pivot_df != 0).sum().sum())
diff --git a/analysis/analysis.sql b/analysis/analysis.sql
deleted file mode 100644
index 78516d0..0000000
--- a/analysis/analysis.sql
+++ /dev/null
@@ -1,22 +0,0 @@
--- Create and prepare abstraction table
-CREATE TABLE IF NOT EXISTS turn_abs (obs BIGINT, abs BIGINT);
-TRUNCATE TABLE turn_abs;
-ALTER TABLE turn_abs
-SET UNLOGGED;
-DROP INDEX IF EXISTS idx_turn_abs_observation;
-COPY turn_abs (obs, abs)
-FROM 'turn.abstraction.pgcopy' WITH (FORMAT BINARY);
-ALTER TABLE turn_abs
-SET LOGGED;
-CREATE INDEX IF NOT EXISTS idx_turn_abs_observation ON turn_abs (obs);
--- Create and prepare metric table
-CREATE TABLE IF NOT EXISTS turn_met (xab BIGINT, dst REAL);
-TRUNCATE TABLE turn_met;
-ALTER TABLE turn_met
-SET UNLOGGED;
-DROP INDEX IF EXISTS idx_turn_xab_abstraction;
-COPY turn_met (xab, dst)
-FROM 'turn.metric.pgcopy' WITH (FORMAT BINARY);
-ALTER TABLE turn_met
-SET LOGGED;
-CREATE INDEX IF NOT EXISTS idx_turn_xab_abstraction ON turn_met (xab);
diff --git a/analysis/poetry.lock b/analysis/poetry.lock
deleted file mode 100644
index 4ae8518..0000000
--- a/analysis/poetry.lock
+++ /dev/null
@@ -1,872 +0,0 @@
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-
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diff --git a/analysis/pyproject.toml b/analysis/pyproject.toml
deleted file mode 100644
index f7cda7e..0000000
--- a/analysis/pyproject.toml
+++ /dev/null
@@ -1,20 +0,0 @@
-[tool.poetry]
-name = "analysis"
-version = "0.1.0"
-description = ""
-authors = ["Kelechi Ukah <ukahkelechi@gmail.com>"]
-readme = "README.md"
-
-[tool.poetry.dependencies]
-python = "^3.13"
-pandas = "^2.2.3"
-numpy = "^2.1.2"
-matplotlib = "^3.9.2"
-seaborn = "^0.13.2"
-SQLAlchemy = "^2.0.36"
-psycopg2-binary = "^2.9.10"
-
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"