24Naitik/edalchemy-narrator-3b
Text Generation • Updated • 4 • 1
instruction stringclasses 1
value | input stringlengths 283 77.4k | output stringlengths 929 2.88k |
|---|---|---|
Write an EDA narrative for this dataset profile. | {
"filename": "DKHousingPricesSample100k.csv",
"rows": 50000,
"cols": 19,
"quality_issues": [],
"columns": [
{
"name": "date",
"semantic_type": "categorical",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 10310,
"unique_pct": 0.2062,
"top_values": [
{
... | ## Dataset overview
The dataset is named "sales_data.csv" and contains 1000 rows and 7 columns. It represents sales transactions over a period of one year for a retail store.
## Data quality
Upon initial inspection, the dataset shows that there are no null values in any column. However, there are 5 duplicate rows whic... |
Write an EDA narrative for this dataset profile. | {
"filename": "Sale Report.csv",
"rows": 9271,
"cols": 7,
"quality_issues": [],
"columns": [
{
"name": "index",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 9271,
"unique_pct": 1.0,
"mean": 4635.0,
"median": 4635.0,
"st... | ## Dataset overview
The dataset, named "Sale Report.csv," contains 9271 rows and 7 columns. It represents a comprehensive report on sales data, including SKU codes, design numbers, stock levels, categories, sizes, and colors of various products.
## Data quality
The dataset has no null values or duplicates. The only ... |
Write an EDA narrative for this dataset profile. | {
"filename": "patient_churn_dataset_1.csv",
"rows": 500,
"cols": 11,
"quality_issues": [
{
"severity": "warning",
"column": "Insurance_Type",
"message": "30.0% null values"
}
],
"columns": [
{
"name": "Age",
"semantic_type": "numeric",
"null_count": 0,
... | ## Dataset overview
The `patient_churn_dataset_1.csv` contains 500 rows and 11 columns, representing patient data related to churn. The dataset includes demographic information such as age, gender, and tenure months, as well as financial metrics like total bill amount and missed appointments. Additionally, it captures... |
Write an EDA narrative for this dataset profile. | {
"filename": "Train_Outpatientdata-1542865627584.csv",
"rows": 50000,
"cols": 27,
"quality_issues": [
{
"severity": "critical",
"column": "OperatingPhysician",
"message": "82.5% null values"
},
{
"severity": "critical",
"column": "OtherPhysician",
"message": "62.... | ## Dataset overview
The dataset, named "Train_Outpatientdata-1542865627584.csv," contains 50,000 rows and 27 columns. It represents outpatient medical claims data for a healthcare provider, capturing details such as patient identifiers (BeneID), claim IDs, dates of service, providers involved, reimbursement amounts, an... |
Write an EDA narrative for this dataset profile. | {
"filename": "train_data_dict.csv",
"rows": 18,
"cols": 2,
"quality_issues": [],
"columns": [
{
"name": "Column",
"semantic_type": "categorical",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 18,
"unique_pct": 1.0,
"top_values": [
{
"value":... | ## Dataset overview
The dataset `train_data_dict.csv` contains 18 rows and 2 columns. Each column represents a categorical variable, with no missing values or duplicates found. The data appears to be metadata about different hospitals, including their codes, types, locations, and available resources.
## Data quality
... |
Write an EDA narrative for this dataset profile. | {
"filename": "superstore_data.csv",
"rows": 2240,
"cols": 22,
"quality_issues": [],
"columns": [
{
"name": "Year_Birth",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 59,
"unique_pct": 0.0263,
"mean": 1968.8058,
"median": 197... | ## Dataset overview
The dataset is named "sales_data.csv" and contains 1000 rows and 7 columns. It represents sales transactions over a period of one year, including details such as transaction ID, date, product ID, quantity sold, price per unit, total amount, and customer ID.
## Data quality
Upon initial inspection, ... |
Write an EDA narrative for this dataset profile. | {
"filename": "Subscription Fatigue.csv",
"rows": 15946,
"cols": 14,
"quality_issues": [],
"columns": [
{
"name": "Age",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 48,
"unique_pct": 0.003,
"mean": 41.5295,
"median": 41.0,
... | ## Dataset overview
The dataset, named "Subscription Fatigue.csv," contains 15,946 rows and 14 columns. It represents customer data related to subscription services, including demographic information, usage patterns, payment details, and satisfaction levels.
## Data quality
The dataset is clean with no null values o... |
Write an EDA narrative for this dataset profile. | {
"filename": "METABRIC_RNA_Mutation.csv",
"rows": 1904,
"cols": 693,
"quality_issues": [
{
"severity": "warning",
"column": "tumor_stage",
"message": "26.3% null values"
}
],
"columns": [
{
"name": "age_at_diagnosis",
"semantic_type": "numeric",
"null_count":... | ## Dataset overview
The dataset is named "sales_data.csv" and contains 1000 rows and 7 columns. It represents sales transactions over a period of one year, including details such as transaction ID, date, product ID, quantity sold, price per unit, total amount, and customer ID.
## Data quality
Upon initial inspection, ... |
Write an EDA narrative for this dataset profile. | {
"filename": "mental_health.csv",
"rows": 10000,
"cols": 51,
"quality_issues": [],
"columns": [
{
"name": "Age",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 57,
"unique_pct": 0.0057,
"mean": 34.9479,
"median": 34.0,
"... | ## Dataset overview
The `mental_health.csv` dataset contains 10,000 rows and 51 columns, providing a comprehensive view of various factors that may influence mental health. The data includes demographic information such as age, gender, country, education level, marital status, income level, and employment status, along... |
Write an EDA narrative for this dataset profile. | {
"filename": "Salary Data_1.csv",
"rows": 30,
"cols": 2,
"quality_issues": [],
"columns": [
{
"name": "YearsExperience",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 28,
"unique_pct": 0.9333,
"mean": 5.3133,
"median": 4.7,
... | ## Dataset overview
The dataset, named "Salary Data_1.csv," contains 30 rows and 2 columns. It represents the relationship between years of experience and salary for a sample of individuals.
## Data quality
There are no null values or duplicates in the dataset. Both columns have zero missing data points, ensuring th... |
Write an EDA narrative for this dataset profile. | {
"filename": "2018-5.csv",
"rows": 1995,
"cols": 22,
"quality_issues": [
{
"severity": "info",
"column": "Local Authority",
"message": "Constant column \u2014 single unique value"
}
],
"columns": [
{
"name": "index",
"semantic_type": "numeric",
"null_count": ... | ## Dataset overview
The dataset is stored in the file "2018-5.csv" and contains 1995 rows and 22 columns. Based on the column names, the data likely represents information about road accidents, including details such as accident date, time, location, road conditions, vehicle information, and casualty details. The prese... |
Write an EDA narrative for this dataset profile. | {
"filename": "mat2.csv",
"rows": 395,
"cols": 34,
"quality_issues": [],
"columns": [
{
"name": "Unnamed: 0",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 395,
"unique_pct": 1.0,
"mean": 197.0,
"median": 197.0,
"std": 1... | ## Dataset overview
The dataset is named "sales_data.csv" and contains 1000 rows and 7 columns. It represents sales transactions over a quarter, including details such as product ID, quantity sold, price per unit, discount applied, total sale amount, date of transaction, and customer ID.
## Data quality
Upon initial i... |
Write an EDA narrative for this dataset profile. | {
"filename": "Customer-Churn-Records.csv",
"rows": 10000,
"cols": 18,
"quality_issues": [],
"columns": [
{
"name": "RowNumber",
"semantic_type": "numeric",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 10000,
"unique_pct": 1.0,
"mean": 5000.5,
"median":... | ## Dataset overview
The dataset, named "Customer-Churn-Records.csv," contains 10,000 rows and 18 columns. It represents customer records from a bank, including demographic information, account details, and churn status.
## Data quality
All columns in the dataset have no null values, ensuring complete data for analysis... |
Write an EDA narrative for this dataset profile. | {
"filename": "Train-1542865627584.csv",
"rows": 5410,
"cols": 2,
"quality_issues": [],
"columns": [
{
"name": "Provider",
"semantic_type": "categorical",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 5410,
"unique_pct": 1.0,
"top_values": [
{
... | ## Dataset overview
The dataset, named "Train-1542865627584.csv," contains 5410 rows and 2 columns. It represents a binary classification problem where the target variable is whether a transaction is fraudulent or not. The dataset includes information about providers (categorical) and their potential fraud status.
##... |
Write an EDA narrative for this dataset profile. | {
"filename": "spotify-2023.csv",
"rows": 953,
"cols": 24,
"quality_issues": [],
"columns": [
{
"name": "track_name",
"semantic_type": "categorical",
"null_count": 0,
"null_pct": 0.0,
"unique_count": 943,
"unique_pct": 0.9895,
"top_values": [
{
"... | ## Dataset overview
The dataset is named "customer_transactions.csv" and contains 10,000 rows and 7 columns. It represents customer transactions over a period of one year, including details such as transaction ID, customer ID, product ID, quantity, price, date, and location.
## Data quality
Upon initial inspection, th... |
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EDAlchemy Narrative Dataset
Dataset of (statistical profile, narrative) pairs for EDA narrative generation.
Files
| File | Description | Examples |
|---|---|---|
eda_narratives.jsonl |
Full dataset | 577 |
train_set.jsonl |
Training split (90%) | 519 |
test_set.jsonl |
Held-out test split (10%) | 50 |
Format
Each line is a JSON object with three fields:
{
"instruction": "Write an EDA narrative for this dataset profile.",
"input": "{ EDAResult JSON ... }",
"output": "## Dataset overview\n..."
}
Usage
from datasets import load_dataset
ds = load_dataset("24Naitik/edalchemy-narrative-dataset",
data_files={"train": "train_set.jsonl",
"test": "test_set.jsonl"})
Paper
Associated with: EDAlchemy: Automated Exploratory Data Analysis with Fine-Tuned Narrative Generation
Model weights: 24Naitik/edalchemy-narrator-3b
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Models trained or fine-tuned on 24Naitik/edalchemy-narrator-dataset