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Datasets:
Tarakeshwaran
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Hackathon_Stock_Prediction

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Auto-converted to Parquet
Date
stringlengths
8
10
Open
float64
23.9
58.6
High
float64
23.9
58.7
Low
float64
23.9
57.7
Volume
int64
2
116k
OpenInt
int64
0
0
Close
float64
23.9
58.4
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Stock Market Dataset

Description

This dataset contains stock market data for a specific stock over a period of time. The dataset includes daily stock prices and trading information, which can be used for financial analysis, time series forecasting, and stock price prediction.

Dataset Details

Columns:

  • Date: The trading date (MM/DD/YYYY format).
  • Open: The opening price of the stock on that day.
  • High: The highest price reached during the trading day.
  • Low: The lowest price reached during the trading day.
  • Volume: The number of shares traded on that day.
  • OpenInt: Open interest (often used in derivatives markets; for stocks, this might not be relevant).
  • Close: The closing price of the stock on that day.

Notes:

  • The column Unnamed: 6 contains only NaN values and should be ignored.
  • The dataset contains 1,582 entries.

Use Cases

  • Stock price trend analysis.
  • Predictive modeling using machine learning.
  • Time series forecasting for financial markets.

How to Use

You can load the dataset using the datasets library: 

from datasets import load_dataset

dataset = load_dataset("Tarakeshwaran/Hackathon_Stock_Prediction")
print(dataset)
Downloads last month
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Size of downloaded dataset files:
56.7 kB
Size of the auto-converted Parquet files:
56.7 kB
Number of rows:
1,582