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diff --git a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md new file mode 100644 index 0000000..caddb11 --- /dev/null +++ b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md @@ -0,0 +1,31 @@ +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. + +[TimeStampedBuffer](/argaze/#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| +|... |... |... |
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