This is the official implementation of the DataFrame specification provided by Raven Computing.
## Getting Started
Install via:
```
pip install raven-pydf
```
After installation you can use the entire DataFrame API by importing one class:
```python
from raven.struct.dataframe import DataFrame
# read a DataFrame file into memory
df = DataFrame.read("/path/to/myFile.df")
# show the first 10 rows on stdout
print(df.head(10))
```
Alternatively, you can import all concrete Column types directly, for example:
```python
from raven.struct.dataframe import (DefaultDataFrame,
IntColumn,
DoubleColumn,
StringColumn)
# create a DataFrame with 3 columns and 3 rows
df = DefaultDataFrame(
IntColumn("A", [1, 2, 3]),
DoubleColumn("B", [4.4, 5.5, 6.6]),
StringColumn("C", ["cat", "dog", "horse"]))
print(df)
# _| A B C
# 0| 1 4.4 cat
# 1| 2 5.5 dog
# 2| 3 6.6 horse
```
## Compatibility
This library requires **Python3.7** or higher.
Internally, this library uses [Numpy](https://github.com/numpy/numpy) for array operations. The minimum required version is v1.19.0
## Documentation
The unified documentation is available [here](https://www.raven-computing.com/docs/dataframe?language=python).
Additional features implemented in Python are documented in the [Wiki](https://github.com/raven-computing/pydf/wiki).
## License
This library is licensed under the Apache License Version 2 - see the [LICENSE](https://github.com/raven-computing/pydf/blob/master/LICENSE) for details.
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