Update README.md

README.md

@@ -2,7 +2,8 @@
 
 
 # pyinfraformat
-Python library for Finnish Infraformat (version 2.5)
+Python library for reading, writing and analyzing Finnish borehole format Infraformat (version 2.5). 
+Well suited for scientific and research applications.
 
 ## Installation
 
@@ -23,3 +24,56 @@ Library can be installed also by `git clone` / downloading zip.
 To install inplace for development work, use `-e` command.
 
     python -m pip install -e .
+
+## Quickstart
+#### Basic usage
+```python
+import pyinfraformat as pif
+pif.set_logger_level(50) # Suppress non-critical warnings, recommended for large files
+holes = pif.from_infraformat("*.tek")
+holes = holes.project("TM35FIN")
+bounds = holes.bounds
+holes.to_infraformat("holes_tm35fin.tek")
+
+bounds = [6672242-200 ,  385795-200, 6672242 +200,  385795+200]
+gtk_holes = pif.from_gtk_wfs(bounds, "TM35Fin")
+print(gtk_holes) # View holes object
+#Infraformat Holes -object:
+#  Total of 203 holes
+#    - PO ......... 161
+#    - HP .........  13
+#    - PA .........  12
+#    - NO .........   2
+#    - NE .........   1
+#    - KE .........   5
+#    - KR .........   9
+
+
+html_map = gtk_holes.plot_map()
+html_map.save("soundings.html")
+html_map # View map in jupyter
+```
+![image](https://github.com/user-attachments/assets/a463e181-4ab4-479d-94f6-edcb19c0f598)
+
+```python
+hole_figure = gtk_holes[10].plot()
+hole_figure # View hole in jupyter
+```
+
+![image](https://github.com/user-attachments/assets/33b9c797-b084-44b2-88c8-dadd15fc540f)
+
+#### Plot histograms from labratory tests
+```python
+import pandas as pd
+bounds = [6672242-2000 ,  385795-2000, 6672242 +2000,  385795+2000]
+gtk_holes = pif.from_gtk_wfs(bounds, "TM35FIN", maxholes=25_000)
+labratory_tests = gtk_holes.filter_holes(hole_type=["NO", "NE"], start="1990-01-01")
+df = labratory_tests.get_dataframe()
+df['data_Soil type'] = df['data_Soil type'].astype("string")
+clay_samples = df[df['data_Soil type'].str.endswith("Sa", na=False)].reset_index()
+clay_samples['data_Laboratory w'] = pd.to_numeric(clay_samples['data_Laboratory w'])
+fig = clay_samples['data_Laboratory w'].plot.hist(bins='fd')
+fig.set_title("Clay samples water content, %")
+fig
+```
+![image](https://github.com/user-attachments/assets/e3e6030b-ccfc-4c59-9929-40a7f9900fa4)