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---
title: Pandas DataFrame conversion
---
Pandas DataFrame conversion
===========================
A [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutorials/01_table_oriented.html#min-tut-01-tableoriented) is a python data structure allowing powerful table processings.
## Export as dataframe
[TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) instance can be converted into dataframe provided that data values are stored as dictionaries.
```python
from argaze import DataStructures
# Create a timestamped data buffer
ts_data = DataStructures.TimeStampedBuffer()
# Store various data as dictionary
ts_data[10] = {"A_key": 0, "B_key": 0.123}}
ts_data[20] = {"A_key": 4, "B_key": 0.567}}
ts_data[30] = {"A_key": 8, "B_key": 0.901}}
...
# Convert timestamped data buffer into dataframe
ts_buffer_dataframe = ts_buffer.as_dataframe()
```
ts_buffer_dataframe would look like:
|timestamp|A_key|B_key|
|:--------|:----|:----|
|10 |0 |0.123|
|20 |4 |0.567|
|30 |8 |0.901|
|... |... |... |
## Import from dataframe
Reversely, [TimeStampedBuffer](../../argaze.md/#argaze.DataStructures.TimeStampedBuffer) instance can be created from dataframe, as a result of which each dataframe columns label will become a key of data value dictionary. Notice that the column containing timestamp values have to be called 'timestamp'.
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