Update readme

README.md

@@ -1,32 +1,34 @@
 # Hackathon: Gitcoin Open Data Science Hackathon : [Sybil Slayer](https://gitcoin.co/issue/29389#) 
 
-The data created for the analysis is available here on [HugginFace](https://huggingface.co/datasets/Poupou/Gitcoin-ODS-Hackhaton-GR15) 
+The data created for the analysis is available here on [Hugging Face](https://huggingface.co/datasets/Poupou/Gitcoin-ODS-Hackhaton-GR15) 
 
-The report is in the github repo [A time series analysis of gitcoin grants contributors to Grant 15](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/A%20time%20series%20analysis%20of%20gitcoin%20grants%20contributors%20to%20Grant%2015.pdf)
-
-To run the jupyter notebook please put the feature dataset in a data folder as follow as:
-And to retrieve the transactions the hackathon-contributions-dataset_v2.csv in the data folder
+The report is in the github repo **[A time series analysis of gitcoin grants contributors to Grant 15](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/A%20time%20series%20analysis%20of%20gitcoin%20grants%20contributors%20to%20Grant%2015.pdf)**
 
+To run the jupyter notebook please put the features datasets and the `hackathon-contributions-dataset_v2.csv` as shown in the directory and file structure below:
 
+```
 data
-
-    |___features
-         |____ eth_polygon
-                  |___features_eth_polygon.csv    
-        
-         |____eth_std
-                  |___features_eth_std.csv      
-    |___ hackathon-contributions-dataset_v2.csv
+  +----features
+          +----- eth_polygon
+                    +----- features_eth_polygon.csv    
+          +----- eth_std
+                    +----- features_eth_std.csv      
+  +----- hackathon-contributions-dataset_v2.csv
+```
 
 Use requirements to install the libraries:
 `pip install requirements.txt`
 
 
-The main jupyter notebook used to create the report is [k_mean_eth](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/jupyter/10_28_k_mean_eth.ipynb).
+The main jupyter notebook used to create the report is **[k_mean_eth](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/jupyter/10_28_k_mean_eth.ipynb)**.
 Be careful before running it is memory heavy because it automatically exports more than 150 charts.
+
 The [k_mean_polygon](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/jupyter/10_28_k_mean_polygon_new.ipynb) notebook is similar and produces the results for the polygon transactions.
+
 The [agglomerative_eth](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/jupyter/10_29_agglomerative_eth_new.ipynb) file shows the results in the case of the agglomerative clustering.
 
+An example of clustering for Ethereum is provided in [eth_std_clusters.csv](https://github.com/poupou-web3/GC-ODS-Sybil/blob/main/eth_std_clusters.csv), please mind that it was added after the report writings and thus the seed used for K-means was not the same, thus cluster names are different from the one used in the report. 
+
 ## Re-creating the data sets
 ### For transactions
 For Etherscan run `src\main\extract_etherscan_txs.py` 
@@ -39,4 +41,3 @@ Parameters are hard coded and should be modified!
 run `src\main\features\create_feature_df.py`
 Parameters are hard coded and should be modified! You can change the tx_chain parameter to select the network.
 
-