From 9f04fafe42fd6436bec09696e1bc8b2abc496cc4 Mon Sep 17 00:00:00 2001
From: Charles <sircharlesaze@gmail.com>
Date: Sat, 25 Jan 2020 14:16:00 +0100
Subject: Dataset parent of Analysis, scatter plot and pair_plot dirty scripts

---
 src/analysis.py     | 29 ++++++++++++++++++++++++++---
 src/dataset.py      | 21 +++++++++++++++++++++
 src/describe.py     | 15 +++------------
 src/pair_plot.py    |  6 ++++++
 src/scatter_plot.py |  6 ++++++
 5 files changed, 62 insertions(+), 15 deletions(-)
 create mode 100644 src/dataset.py
 create mode 100644 src/pair_plot.py
 create mode 100644 src/scatter_plot.py

(limited to 'src')

diff --git a/src/analysis.py b/src/analysis.py
index abc0ffb..b6c9eb9 100644
--- a/src/analysis.py
+++ b/src/analysis.py
@@ -1,12 +1,14 @@
 import numpy as np
 import pandas as pd
+import matplotlib.pyplot as plt
 
+from dataset import Dataset
 import dslr_stat
 
 
-class Analysis:
-    def __init__(self, df):
-        self.df = df
+class Analysis(Dataset):
+    def __init__(self, path):
+        super().__init__(path)
 
     def describe(self):
         desc_df = pd.DataFrame(
@@ -24,3 +26,24 @@ class Analysis:
             desc_df.loc['75%', col] = dslr_stat.q75(self.df[col])
             desc_df.loc['Max', col] = dslr_stat.max(self.df[col])
         print(desc_df)
+
+    def hist(self):
+        pass
+
+    def scatter(self):
+        plt.scatter(self.df['astronomy'], self.df['defense_against_the_dark_arts'])
+        plt.show()
+
+    def pair_plot(self):
+        scores = self.df_scores
+        fig, axis = plt.subplots(nrows=scores.shape[1],
+                                 ncols=scores.shape[1])
+        for i, col in enumerate(scores.columns):
+            for j, pair_col in enumerate(scores.columns):
+                ax = axis[i, j]
+                if pair_col == col:
+                    ax.hist(scores)
+                    continue
+                ax.scatter(scores[col], scores[pair_col])
+        plt.tight_layout()
+        plt.show()
diff --git a/src/dataset.py b/src/dataset.py
new file mode 100644
index 0000000..650d334
--- /dev/null
+++ b/src/dataset.py
@@ -0,0 +1,21 @@
+import pandas as pd
+
+
+class Dataset:
+    def __init__(self, path):
+        self.path = path
+        try:
+            self.df = pd.read_csv(path)
+        except FileNotFoundError:
+            raise "Couldn't find dataset at: {}".format(path)
+        self.df.drop(columns=['Index'], inplace=True)
+        self.df.dropna(inplace=True)
+        self.df.columns = self.df.columns.str.lower()
+        self.df.columns = self.df.columns.str.replace(' ', '_')
+        self.df.rename(columns={'hogwarts_house': 'house'}, inplace=True)
+
+    @property
+    def df_scores(self):
+        return self.df.loc[:, 'arithmancy':'flying']
+
+
diff --git a/src/describe.py b/src/describe.py
index 7a968f1..4a3c5bc 100644
--- a/src/describe.py
+++ b/src/describe.py
@@ -1,20 +1,11 @@
 import sys
 
-import pandas as pd
 from analysis import Analysis
 
 
 if __name__ == "__main__":
     if len(sys.argv) != 2:
-        print("Usage: {} dataset_path".format(sys.argv[0]))
-        sys.exit(1)
-    try:
-        df = pd.read_csv(sys.argv[1])
-    except FileNotFoundError:
-        print("Could not find dataset at: {}".format(sys.argv[1]))
-        sys.exit(1)
-    df = df.loc[:, 'Arithmancy':'Flying']
-    df.dropna(inplace=True)
-    a = Analysis(df)
+        raise "Usage: {} dataset_path".format(sys.argv[0])
+    a = Analysis(sys.argv[1])
     a.describe()
-    print(df.describe())
+    print(a.df_scores.describe())
diff --git a/src/pair_plot.py b/src/pair_plot.py
new file mode 100644
index 0000000..bf0c632
--- /dev/null
+++ b/src/pair_plot.py
@@ -0,0 +1,6 @@
+from analysis import Analysis
+
+
+if __name__ == '__main__':
+    a = Analysis('../datasets/dataset_train.csv')
+    a.pair_plot()
diff --git a/src/scatter_plot.py b/src/scatter_plot.py
new file mode 100644
index 0000000..74e0384
--- /dev/null
+++ b/src/scatter_plot.py
@@ -0,0 +1,6 @@
+from analysis import Analysis
+
+
+if __name__ == '__main__':
+    a = Analysis('../datasets/dataset_train.csv')
+    a.scatter()
-- 
cgit