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-rw-r--r--docs/user_guide/timestamped_data/pandas_dataframe_conversion.md4
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
index eaa7b69..7614e73 100644
--- a/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
+++ b/docs/user_guide/timestamped_data/pandas_dataframe_conversion.md
@@ -9,7 +9,7 @@ A [Pandas DataFrame](https://pandas.pydata.org/docs/getting_started/intro_tutori
## Export as dataframe
-[TimeStampedBuffer](../../../argaze/#argaze.DataStructures.TimeStampedBuffer) instance can be converted into dataframe provided that data values are stored as dictionaries.
+[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
@@ -38,4 +38,4 @@ ts_buffer_dataframe would look like:
## 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'.
+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'.