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analysis.py
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analysis.py
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import streamlit as st
import matplotlib.pyplot as plt
import pandas as pd
# file which holds the class for the analysis section
class Analysis_class:
def __init__(self, workouts):
self.workouts = workouts
def parse_reps(self,reps_str):
"""Parse the reps string into a list of integers."""
# Removing brackets and splitting by comma
reps_str = reps_str.replace('[', '').replace(']', '')
reps_list = []
for rep in reps_str.split(","):
print(rep)
try:
reps_list.append(int(rep))
except:
continue
print(reps_list)
return reps_list
def parse_weights(self, weights_str):
"""Parse the weights string into a list of integers."""
return [int(weight) for weight in weights_str.split(',') if weight]
def analyze_workout(self, workouts, exercise_name):
"""Extract and analyze workout data for the selected exercise."""
weight, reps, dates, table_w = [], [], [], []
for workout_day in workouts:
for workout in workout_day:
if exercise_name.lower() in workout["Exercise Name"].lower():
table_w.append(workout)
weights = self.parse_weights(workout["Weight"])
reps_list = self.parse_reps(workout["Reps"])
if len(weights) == len(reps_list):
weight.extend(weights)
reps.extend(reps_list)
dates.extend([workout["Date"]] * len(weights))
return weight, reps, dates, table_w
def display_analysis(self,weight, reps, dates, table_w):
"""Display analysis results using Streamlit."""
if not weight:
st.text("No data found for the selected exercise.")
return
st.text("Table of all entries with that exercise:")
st.table(table_w)
# Data preparation for plotting
df = pd.DataFrame({
"Date": pd.to_datetime(dates, format='%m/%d/%y'),
"Weight": weight,
"Reps": reps
}).sort_values('Date')
# Summary statistics
st.markdown("### Summary Statistics")
st.text(f"Max Weight: {df['Weight'].max()}")
st.text(f"Min Weight: {df['Weight'].min()}")
st.text(f"Number of Workouts: {len(df['Weight'])}")
st.text(f"Average Weight: {df['Weight'].mean():.2f}")
# Plot weight over time
st.title('Weight Over Time')
plt.figure(figsize=(10, 5))
plt.plot(df['Date'], df['Weight'], marker='o')
plt.xlabel('Date')
plt.ylabel('Weight')
plt.title('Weight Tracking')
plt.grid(True)
plt.xticks(rotation=45)
st.pyplot(plt)
# Bar chart for weights
st.title("Weight over time (bar chart)")
st.bar_chart(df['Weight'])
# Reps vs Weight
st.title('Reps vs Weight')
plt.figure(figsize=(10, 5))
plt.scatter(df['Reps'], df['Weight'], marker='o')
plt.xlabel('Reps')
plt.ylabel('Weight')
plt.title('Reps vs Weight')
plt.grid(True)
st.pyplot(plt)