# Apply each value in a column against the whole column
```python
pip install a-pandas-ex-apply-against-all
```
```python
from a_pandas_ex_apply_against_all import pd_add_apply_each
import pandas as pd
pd_add_apply_each()
df = pd.read_csv(
"https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv"
)
df1 = df.PassengerId.s_apply_each(
expression="str(x) + str(y)", # use always x/y in your expression
exception_value=pd.NA,
diagonal_value=pd.NA,
print_exception=True,
)
print(df1)
0 1 2 3 4 ... 886 887 888 889 890
0 <NA> 12 13 14 15 ... 1887 1888 1889 1890 1891
1 21 <NA> 23 24 25 ... 2887 2888 2889 2890 2891
2 31 32 <NA> 34 35 ... 3887 3888 3889 3890 3891
3 41 42 43 <NA> 45 ... 4887 4888 4889 4890 4891
4 51 52 53 54 <NA> ... 5887 5888 5889 5890 5891
.. ... ... ... ... ... ... ... ... ... ... ...
886 8871 8872 8873 8874 8875 ... <NA> 887888 887889 887890 887891
887 8881 8882 8883 8884 8885 ... 888887 <NA> 888889 888890 888891
888 8891 8892 8893 8894 8895 ... 889887 889888 <NA> 889890 889891
889 8901 8902 8903 8904 8905 ... 890887 890888 890889 <NA> 890891
890 8911 8912 8913 8914 8915 ... 891887 891888 891889 891890 <NA>
[891 rows x 891 columns]
# If you use a non-built-in function, you have to pass it as an argument, and use it as "func" in your expression
# An example using shapely (merging different polygons)
from shapely.ops import unary_union
import shapely
polyshape = []
for k in range(10):
xmin = k * 10 + 5
ymin = k * 10 + 5
xmax = k * 20 + 10
ymax = k * 20 + 10
coordsalls = [[xmin, ymin], [xmax, ymin], [xmax, ymax], [xmin, ymax], [xmin, ymin]]
po = shapely.geometry.Polygon(coordsalls)
polyshape.append(po)
df2 = pd.DataFrame(polyshape)
df2
Out[7]:
0
0 POLYGON ((5 5, 10 5, 10 10, 5 10, 5 5))
1 POLYGON ((15 15, 30 15, 30 30, 15 30, 15 15))
2 POLYGON ((25 25, 50 25, 50 50, 25 50, 25 25))
3 POLYGON ((35 35, 70 35, 70 70, 35 70, 35 35))
4 POLYGON ((45 45, 90 45, 90 90, 45 90, 45 45))
5 POLYGON ((55 55, 110 55, 110 110, 55 110, 55 55))
6 POLYGON ((65 65, 130 65, 130 130, 65 130, 65 65))
7 POLYGON ((75 75, 150 75, 150 150, 75 150, 75 75))
8 POLYGON ((85 85, 170 85, 170 170, 85 170, 85 85))
9 POLYGON ((95 95, 190 95, 190 190, 95 190, 95 95))
df1 = df2[0].s_apply_each(
expression="func([x,y]) if x.intersects(y) else x", # use always x/y in your expression
func=unary_union,
exception_value=pd.NA,
diagonal_value=pd.NA,
print_exception=True,
ignore_exceptions=True
)
Out[8]:
0 ... 9
0 <NA> ... POLYGON ((5 5, 10 5, 10 10, 5 10, 5 5))
1 POLYGON ((15 15, 30 15, 30 30, 15 30, 15 15)) ... POLYGON ((15 15, 30 15, 30 30, 15 30, 15 15))
2 POLYGON ((25 25, 50 25, 50 50, 25 50, 25 25)) ... POLYGON ((25 25, 50 25, 50 50, 25 50, 25 25))
3 POLYGON ((35 35, 70 35, 70 70, 35 70, 35 35)) ... POLYGON ((35 35, 70 35, 70 70, 35 70, 35 35))
4 POLYGON ((45 45, 90 45, 90 90, 45 90, 45 45)) ... POLYGON ((45 45, 90 45, 90 90, 45 90, 45 45))
5 POLYGON ((55 55, 110 55, 110 110, 55 110, 55 55)) ... POLYGON ((110 55, 55 55, 55 110, 95 110, 95 19...
6 POLYGON ((65 65, 130 65, 130 130, 65 130, 65 65)) ... POLYGON ((130 65, 65 65, 65 130, 95 130, 95 19...
7 POLYGON ((75 75, 150 75, 150 150, 75 150, 75 75)) ... POLYGON ((150 75, 75 75, 75 150, 95 150, 95 19...
8 POLYGON ((85 85, 170 85, 170 170, 85 170, 85 85)) ... POLYGON ((170 85, 85 85, 85 170, 95 170, 95 19...
9 POLYGON ((95 95, 190 95, 190 190, 95 190, 95 95)) ... <NA>
[10 rows x 10 columns]
```
Raw data
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