From 67fc8a3707ab8a9ff981fa04356e21170cd3c5a0 Mon Sep 17 00:00:00 2001
From: Alexander Shervud <alexander.shervud@uni-potsdam.de>
Date: Wed, 12 Jul 2023 17:23:46 +0200
Subject: [PATCH] Added Formatting and PyCodeStyle
---
src/Plotter.py | 41 +++++++++++++++++++++++------------------
1 file changed, 23 insertions(+), 18 deletions(-)
diff --git a/src/Plotter.py b/src/Plotter.py
index 5ff1486..c9055be 100644
--- a/src/Plotter.py
+++ b/src/Plotter.py
@@ -4,41 +4,46 @@ import pandas as pd
import seaborn as sns
from .Dataset import Dataset
+
class Plotter:
def __init__(self, dataset: Dataset):
self.ds = dataset
self.df = dataset.get_dataframe()
-
def customize_plot(self, fig, ax, styling_params):
- if styling_params.get('title'):
+ if styling_params.get("title"):
ax.set_title(styling_params["title"])
-
+
def distribution_plot(self, target):
- grouped_data = self.df.groupby(target).size()
+ grouped_data = self.df.groupby(target).size()
plt.barh(grouped_data.index, grouped_data.values)
- print(str(grouped_data), str(grouped_data.index), str(grouped_data.values))
+ print(
+ str(grouped_data),
+ str(grouped_data.index),
+ str(grouped_data.values),
+ )
plt.xlabel("Size")
plt.ylabel(target)
plt.title(f"Distribution of {target}")
-
-
- def plot_categorical_bar_chart(self, category1, category2, styling_params = {}):
+
+ def plot_categorical_bar_chart(
+ self, category1, category2, styling_params={}
+ ):
ct = pd.crosstab(self.df[category1], self.df[category2])
# Calculate percentages by row
- ct_percent = ct.apply(lambda r: r/r.sum() * 100, axis=0)
+ ct_percent = ct.apply(lambda r: r / r.sum() * 100, axis=0)
fig, ax = plt.subplots()
self.customize_plot(fig, ax, styling_params)
- ct_percent.plot(kind='bar', ax=ax)
+ ct_percent.plot(kind="bar", ax=ax)
-
- def plot_categorical_boxplot(self, target, category, styling_params = {}):
+ def plot_categorical_boxplot(self, target, category, styling_params={}):
fig, ax = plt.subplots()
self.customize_plot(fig, ax, styling_params)
- sns.boxplot(x=category,y=target,data=self.df, palette='rainbow')
-
+ sns.boxplot(x=category, y=target, data=self.df, palette="rainbow")
- def plot_categorical_histplot(self, target, category, styling_params = {}, bins= 30):
+ def plot_categorical_histplot(
+ self, target, category, styling_params={}, bins=30
+ ):
uniques = self.ds.get_unique_column_values(category)
fig, ax = plt.subplots()
self.customize_plot(fig, ax, styling_params)
@@ -48,11 +53,11 @@ class Plotter:
ax.hist(
anx_score,
weights=anx_score_weights,
- bins = bins,
+ bins=bins,
alpha=0.5,
)
- def plot_scatterplot(self, target1, target2, styling_params = {}):
+ def plot_scatterplot(self, target1, target2, styling_params={}):
fig, ax = plt.subplots()
self.customize_plot(fig, ax, styling_params)
- ax.scatter(self.df[target1], self.df[target2])
\ No newline at end of file
+ ax.scatter(self.df[target1], self.df[target2])
--
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