added new dataset.Removed data folder

app.py

@@ -1,7 +1,11 @@
 import gradio as gr
 import pandas as pd
 import duckdb
+import gzip
+import shutil
+import os
 import logging
+from huggingface_hub import hf_hub_download
 from tabs.trades import (
     prepare_trades,
     get_overall_trades,
@@ -66,6 +70,71 @@ def get_logger():
 logger = get_logger()
 
 
+def load_all_data():
+    # error by markets
+    errors_df = hf_hub_download(
+        repo_id="valory/Olas-predict-dataset",
+        filename="error_by_markets.parquet",
+        repo_type="dataset",
+    )
+
+    df1 = pd.read_parquet(errors_df)
+
+    # all trades profitability
+    # Download the compressed file
+    gz_file_path = hf_hub_download(
+        repo_id="valory/Olas-predict-dataset",
+        filename="all_trades_profitability.parquet.gz",
+        repo_type="dataset",
+    )
+
+    # Create path for decompressed file
+    parquet_file_path = gz_file_path.replace(".gz", "")
+
+    # Decompress the file
+    with gzip.open(gz_file_path, "rb") as f_in:
+        with open(parquet_file_path, "wb") as f_out:
+            shutil.copyfileobj(f_in, f_out)
+
+    # Now read the decompressed parquet file
+    df2 = pd.read_parquet(parquet_file_path)
+
+    # tools_accuracy
+    tools_accuracy = pd.read_csv(
+        "https://huggingface.co/datasets/valory/Olas-predict-dataset/raw/main/tools_accuracy.csv",
+        sep=",",
+    )
+    df3 = pd.DataFrame(tools_accuracy)
+
+    # invalid trades
+    invalid_df = hf_hub_download(
+        repo_id="valory/Olas-predict-dataset",
+        filename="invalid_trades.parquet",
+        repo_type="dataset",
+    )
+
+    df4 = pd.read_parquet(invalid_df)
+
+    # unknown traders
+    unknown_df = hf_hub_download(
+        repo_id="valory/Olas-predict-dataset",
+        filename="unknown_traders.parquet",
+        repo_type="dataset",
+    )
+
+    df5 = pd.read_parquet(unknown_df)
+
+    # winning_df.parquet
+    winning_df = hf_hub_download(
+        repo_id="valory/Olas-predict-dataset",
+        filename="winning_df.parquet",
+        repo_type="dataset",
+    )
+
+    df6 = pd.read_parquet(winning_df)
+    return df1, df2, df3, df4, df5, df6
+
+
 def get_all_data():
     """
     Get all data from the parquet files
@@ -130,7 +199,7 @@ def prepare_data():
         invalid_trades,
         unknown_trades,
         winning_df,
-    ) = get_all_data()
+    ) = load_all_data()
     print(trades_df.info())
 
     trades_df = prepare_trades(trades_df)

data/all_trades_profitability.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6a9fa6fcb351f21334b3a79194c82d9b344be2549d7cd9398c3dea84646291dc
-size 11576111

data/daily_info.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5ff013973cd9530e4eb535ea4f9c3db3cee90f6be70800682eefa7b37f78388b
-size 2709198

data/error_by_markets.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:026835121a261b46a391e397160f878413bd1f337903324bb1cd6ef88bc2d90c
-size 12990

data/invalid_trades.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8a47b04bfae501edb6051f0089117b51fc96cdb4eeb4ad5ef3ebfbcd7ee19590
-size 755966

data/outliers.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:81f07e9f5a1ad5c39b73068888e94260f86782f4f9511cbf548cd366ff827218
-size 19361

data/service_map.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:da35d7c845c32bc90c5f298210458dfa01b8745bf95bd23b62a49c044ca06ac7
-size 167913

data/tools_accuracy.csv

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3a26951af78022999c8651278aff7a96ed271a6d325907096982b5333a7af7b7
-size 1099

data/unknown_traders.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cd2aa16659f93661ac3e9744f55ba17d921bf5f65c843a60f01232dd587254bf
-size 365566

data/winning_df.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:10f727eac679040aa5f1dc1856580010c315b3f72810cdbcaa6175f5a8343c0e
-size 12528