dnirfana commited on
Commit
18630cd
1 Parent(s): 8642210

change sns.pairplot to st.image

Browse files
Files changed (1) hide show
  1. eda.py +2 -3
eda.py CHANGED
@@ -16,7 +16,7 @@ def loading():
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  @st.cache_data
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  def load_data():
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- return pd.read_csv('Transactions Data.csv')
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  def app():
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  st.title('Exploratory Data Analysis')
@@ -329,8 +329,7 @@ def app():
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  # Pairplot to visualize relationships
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  st.subheader('Pairplot of Numeric Variables')
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  with st.spinner('Loading...'):
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- fig = sns.pairplot(df[['amount', 'oldbalanceOrg', 'newbalanceOrig', 'oldbalanceDest', 'newbalanceDest']])
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- st.pyplot(fig)
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  st.write('The pair plot provides a detailed view of the relationships between the numeric variables: `amount`, `oldbalanceOrg`, `newbalanceOrig`, `oldbalanceDest`, and `newbalanceDest`.')
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  st.markdown('- **Strong Linear Relationships**: There are clear linear relationships between `oldbalanceOrg` and `newbalanceOrig`, as well as between `oldbalanceDest` and `newbalanceDest`. This indicates that the balance before and after transactions are highly correlated.')
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  st.markdown('- **Clustered Data Points**: Most data points are clustered near the lower end of the scales, especially for `amount` and `balances`, suggesting a high frequency of small-value transactions.')
 
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  @st.cache_data
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  def load_data():
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+ return pd.read_csv('../Transactions Data.csv')
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  def app():
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  st.title('Exploratory Data Analysis')
 
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  # Pairplot to visualize relationships
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  st.subheader('Pairplot of Numeric Variables')
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  with st.spinner('Loading...'):
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+ st.image('pairplot.png')
 
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  st.write('The pair plot provides a detailed view of the relationships between the numeric variables: `amount`, `oldbalanceOrg`, `newbalanceOrig`, `oldbalanceDest`, and `newbalanceDest`.')
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  st.markdown('- **Strong Linear Relationships**: There are clear linear relationships between `oldbalanceOrg` and `newbalanceOrig`, as well as between `oldbalanceDest` and `newbalanceDest`. This indicates that the balance before and after transactions are highly correlated.')
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  st.markdown('- **Clustered Data Points**: Most data points are clustered near the lower end of the scales, especially for `amount` and `balances`, suggesting a high frequency of small-value transactions.')