From 0e435f38a00c161fe037948b5df71e093934d6d3 Mon Sep 17 00:00:00 2001
From: Théo de la Hogue
Date: Tue, 11 Jul 2023 16:19:24 +0200
Subject: Documenting from_dataframe methods.

---
 docs/user_guide/gaze_analysis/gaze_position.md        | 19 +++++++++++++++++++
 .../timestamped_data/pandas_dataframe_conversion.md   |  8 +++++++-
 2 files changed, 26 insertions(+), 1 deletion(-)

(limited to 'docs')

diff --git a/docs/user_guide/gaze_analysis/gaze_position.md b/docs/user_guide/gaze_analysis/gaze_position.md
index 9cc7f85..8856bec 100644
--- a/docs/user_guide/gaze_analysis/gaze_position.md
+++ b/docs/user_guide/gaze_analysis/gaze_position.md
@@ -66,3 +66,22 @@ if gaze_position_A.overlap(gaze_position_B, both=True):
         # Do something if A overlaps B AND B overlaps A
         ...
 ```
+
+## Timestamped gaze positions
+
+[TimeStampedGazePositions](../../../argaze/#argaze.GazeFeatures.TimeStampedGazePositions) inherits from [TimeStampedBuffer](../../../argaze/#argaze.DataStructures.TimeStampedBuffer) class to handle especially gaze positions.
+
+### Import from dataframe
+
+It is possible to load timestamped gaze positions from a [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutorials/01_table_oriented.html#min-tut-01-tableoriented) object.
+
+```python
+import pandas
+
+# Load gaze positions from a CSV file into Panda Dataframe
+dataframe = pandas.read_csv('gaze_positions.csv', delimiter="\t", low_memory=False)
+
+# Convert Panda dataframe into TimestampedGazePositions buffer precising the use of each specific column labels
+ts_gaze_positions = GazeFeatures.TimeStampedGazePositions.from_dataframe(dataframe, timestamp = 'Recording timestamp [ms]', x = 'Gaze point X [px]', y = 'Gaze point Y [px]')
+
+```
diff --git a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
index 839460a..eaa7b69 100644
--- a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
+++ b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
@@ -7,6 +7,8 @@ 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/#argaze.DataStructures.TimeStampedBuffer) instance can be converted into dataframe provided that data values are stored as dictionaries.
 
 ```python
@@ -32,4 +34,8 @@ ts_buffer_dataframe would look like:
 |10       |0    |0.123|
 |20       |4    |0.567|
 |30       |8    |0.901|
-|...      |...  |...  |
\ No newline at end of file
+|...      |...  |...  |
+
+## Import from dataframe
+
+Reversely, [TimeStampedBuffer](../../../argaze/#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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