Customer Personality Analysis

abhisheks008 · Jan 25, 2024 · db44c4e · db44c4e
1 parent abb4286
commit db44c4e
Show file tree

Hide file tree

Showing 10 changed files with 6,696 additions and 0 deletions.
diff --git a/Customer Personality Analysis/Dataset/marketing_campaign.csv b/Customer Personality Analysis/Dataset/marketing_campaign.csv
diff --git a/Customer Personality Analysis/Images/Images.png b/Customer Personality Analysis/Images/Images.png
diff --git a/Customer Personality Analysis/Images/expenses.png b/Customer Personality Analysis/Images/expenses.png
diff --git a/Customer Personality Analysis/Images/figure.png b/Customer Personality Analysis/Images/figure.png
diff --git a/Customer Personality Analysis/Images/figure1.png b/Customer Personality Analysis/Images/figure1.png
diff --git a/Customer Personality Analysis/Images/histplot.png b/Customer Personality Analysis/Images/histplot.png
diff --git a/Customer Personality Analysis/Images/marital_status.png b/Customer Personality Analysis/Images/marital_status.png
diff --git a/Customer Personality Analysis/Model/Customer personality Analysis.ipynb b/Customer Personality Analysis/Model/Customer personality Analysis.ipynb
diff --git a/Customer Personality Analysis/README.md b/Customer Personality Analysis/README.md
@@ -0,0 +1,65 @@
+<h1>Customer Personality Analysis</h1>
+
+**GOAL**
+
+To build a machine learning model for predicting the customer's personality on the basis of his daily living.
+
+**DATASET**
+
+https://www.kaggle.com/datasets/imakash3011/customer-personality-analysis
+
+**DESCRIPTION**
+
+To analyze the dataset of customer's personality and build and train the model on the basis of different features and variables.
+
+
+### Visualization and EDA of different attributes:
+
+<img alt="graph" src="./Images/histplot.png">
+
+<img alt="graph" src="./Images/figure1.png">
+
+<img alt="graph" src="./Images/figure.png">
+
+<img alt="graph" src="./Images/expenses.png">
+
+<img alt="graph" src="./Images/Images.png">
+
+<img alt="graph" src="./Images/marital_status.png">
+
+
+**MODEL USED**
+
+| Model             | Shiloutte Score | V Score | Completeness |
+|-------------------|-----------------|---------|--------------|
+| K-Means           | 0.30            | 0.26    | 0.97         |
+| Mean Shift        | 0.18            | 0.23    | 0.96         |
+| Agglometric       | 0.19            | 0.21    | 0.98         |
+| DBSCAN            | -0.33           | 0.26    | 0.97         |
+
+
+
+**WHAT I HAD DONE**
+
+* Load the dataset which contains 2240 entries in it and having 29 columns in it.
+* Checked for missing values and cleaned the data accordingly.
+* Analyzed the data, found insights and visualized them accordingly.
+* Found detailed insights of different columns with target variable using plotting libraries.
+* Train the datasets by different models and saves their accuracies into a dataframe.
+
+
+**LIBRARIES NEEDED**
+
+1. Pandas
+2. Matplotlib
+3. Sklearn
+4. NumPy
+5. Seaborn
+
+
+**CONCLUSION**
+
+Using different clustering models found out the silhouette score, v score and completeness score of the a particular column and the whole dataset.
+
+**Pawas Pandey**
+
diff --git a/Customer Personality Analysis/requirements.txt b/Customer Personality Analysis/requirements.txt
@@ -0,0 +1,4 @@
+matplotlib==3.5.2
+seaborn==0.11.2
+numpy==1.19.2
+pandas==1.4.3