Point Subaccessor#

In geotech-pandas, a point represents the point in which a borehole or a soil profile is located.

In this guide, the basics of the point subaccessor methods are presented. The point subaccessor is a collection of point-related methods intended for managing points in a DataFrame that contains one or more points.

First, we import the necessary libraries,

In [1]: import pandas as pd

In [2]: import geotech_pandas

Next, we create a simple DataFrame with the following data,

In [3]: df = pd.DataFrame(
   ...:     {
   ...:         "point_id": ["BH-1", "BH-1", "BH-1", "BH-2", "BH-2"],
   ...:         "top": [0.0, 1.0, 2.0, 0.0, 1.0],
   ...:         "bottom": [1.0, 2.0, 3.0, 1.0, 5.0],
   ...:         "soil_type": ["sand", "clay", "sand", "sand", "clay"],
   ...:     }
   ...: )
   ...: 

In [4]: df
Out[4]: 
  point_id  top  bottom soil_type
0     BH-1  0.0     1.0      sand
1     BH-1  1.0     2.0      clay
2     BH-1  2.0     3.0      sand
3     BH-2  0.0     1.0      sand
4     BH-2  1.0     5.0      clay

Getting a specific point#

The get_group() method returns a copy of the supplied point_id.

If you somehow forgot the IDs we stored in df earlier, then you can easliy check the list stored in the ids attribute,

In [5]: df.geotech.point.ids
Out[5]: ['BH-1', 'BH-2']

Now, if you wish to get a copy of BH-1,

In [6]: df.geotech.point.get_group("BH-1")
Out[6]: 
  point_id  top  bottom soil_type
0     BH-1  0.0     1.0      sand
1     BH-1  1.0     2.0      clay
2     BH-1  2.0     3.0      sand

On the other hand, getting a copy of BH-2,

In [7]: df.geotech.point.get_group("BH-2")
Out[7]: 
  point_id  top  bottom soil_type
3     BH-2  0.0     1.0      sand
4     BH-2  1.0     5.0      clay

Note

get_group() only returns copies of the sliced DataFrame, so modifying it will not change anything in the original DataFrame.

For example, if we modify the soil type of BH-2 to rock,

In [8]: bh2 = df.geotech.point.get_group("BH-2")

In [9]: bh2.loc[:, "soil_type"] = "rock"

In [10]: bh2
Out[10]: 
  point_id  top  bottom soil_type
3     BH-2  0.0     1.0      rock
4     BH-2  1.0     5.0      rock

Then get a new copy of BH-2 from df,

In [11]: df.geotech.point.get_group("BH-2")
Out[11]: 
  point_id  top  bottom soil_type
3     BH-2  0.0     1.0      sand
4     BH-2  1.0     5.0      clay

As you can see, the DataFrame copy in bh2 was modified, but not the new copy from the source DataFrame. This is because of the Copy-on-Write optimizations in pandas which prevents modifications on copies to reflect on the source. Keep this in mind when modifying copies as it may not be the behavior you want. For more information, see Copy-on-Write (CoW).

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