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Edited ReadME to include URL info #381

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Aug 4, 2021
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Edited ReadME to include URL info #381

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7 changes: 6 additions & 1 deletion README.md
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Expand Up @@ -14,7 +14,7 @@ Getting started only takes a few lines of code ([example csv](https://raw.github
import json
from dataprofiler import Data, Profiler

data = Data("your_file.csv") # Auto-Detect & Load: CSV, AVRO, Parquet, JSON, Text
data = Data("your_file.csv") # Auto-Detect & Load: CSV, AVRO, Parquet, JSON, Text, URL

print(data.data.head(5)) # Access data directly via a compatible Pandas DataFrame

Expand Down Expand Up @@ -169,6 +169,7 @@ The format for an unstructured profile is below:
* Parquet file
* Text file
* Pandas DataFrame
* A URL that points to one of the supported file types above

### Data Types

Expand Down Expand Up @@ -219,6 +220,7 @@ The Data Profiler can profile the following data/file types:
* Parquet file
* Text file
* Pandas DataFrame
* A URL that points to one of the supported file types above

The profiler should automatically identify the file type and load the data into a `Data Class`.

Expand All @@ -239,6 +241,9 @@ parquet_data.data.sort_values(by='name', inplace=True)

# Print the sorted first 10 rows of the parquet data
print(parquet_data.data.head(10))

# Load a json file from a URL, return a JSONData object
json_data = Data('https://github.com/capitalone/DataProfiler/blob/main/dataprofiler/tests/data/json/iris-utf-8.json')
```

If the file type is not automatically identified (rare), you can specify them
Expand Down