a-pandas-ex-column-reduce 0.10

Description:

apandasexcolumnreduce 0.10

Apply reduce against a whole Pandas Series
pip install a-pandas-ex-column-reduce

from a_pandas_ex_column_reduce import pd_add_column_reduce

import pandas as pd

pd_add_column_reduce()

df = pd.read_csv(

"https://raw.githubusercontent.com/pandas-dev/pandas/main/doc/data/titanic.csv"

)

df = df[:10]

result1 = df.PassengerId.s_column_reduce(

expression="str(x) + str(y)", # the expression has to be passed as a string and must contain x/y

own_value_against_own_value=True, # if False: skips when "index of x == index of y"

ignore_exceptions=True, # will ignore the execution of the expression and will go on

print_exceptions=True,

)

print(f"\n\n{result1=}")



result1=0 112345678910

1 212345678910

2 312345678910

3 412345678910

4 512345678910

5 612345678910

6 712345678910

7 812345678910

8 912345678910

9 1012345678910

dtype: object





result2 = df.PassengerId.s_column_reduce(

expression="x + y",

own_value_against_own_value=True,

ignore_exceptions=True,

print_exceptions=True,

)

print(f"\n\n{result2=}")



result2=0 56

1 57

2 58

3 59

4 60

5 61

6 62

7 63

8 64

9 65

dtype: int64





# Updates the column after each iteration

result3 = df.PassengerId.s_column_reduce_update(

expression="x + y if y > 5 else x",

own_value_against_own_value=True,

ignore_exceptions=True,

print_exceptions=True,

)





print(f"\n\n{result3=}")





result3=0 41

1 83

2 167

3 335

4 671

5 1343

6 2681

7 5356

8 10705

9 21402

Name: PassengerId, dtype: int64





# If you use a non-built-in function, you have to pass the function 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)

print(f"\n\n{df2=}")

dfj = df2[0].s_column_reduce(

expression="func([x,y]) if x.intersects(y) else x",

func=unary_union,

own_value_against_own_value=True,

ignore_exceptions=True,

)

print(f"\n\n{dfj=}")

dfj2 = df2[0].s_column_reduce_update(

expression="func([x,y]) if x.intersects(y) else x",

func=unary_union,

own_value_against_own_value=False,

ignore_exceptions=True,

)

print(f"\n\n{dfj2=}")





df2= 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))



dfj=0 POLYGON ((5 5, 5 10, 10 10, 10 5, 5 5))

1 POLYGON ((55 90, 55 110, 65 110, 65 130, 75 13...

2 POLYGON ((45 90, 55 90, 55 110, 65 110, 65 130...

3 POLYGON ((55 90, 55 110, 65 110, 65 130, 75 13...

4 POLYGON ((35 70, 45 70, 45 90, 55 90, 55 110, ...

5 POLYGON ((45 70, 45 90, 55 90, 55 110, 65 110,...

6 POLYGON ((45 70, 45 90, 55 90, 55 110, 65 110,...

7 POLYGON ((45 90, 55 90, 55 110, 65 110, 65 130...

8 POLYGON ((90 55, 90 45, 45 45, 45 90, 55 90, 5...

9 POLYGON ((130 65, 110 65, 110 55, 55 55, 55 11...

dtype: object



dfj2=0 POLYGON ((5 5, 10 5, 10 10, 5 10, 5 5))

1 POLYGON ((45 70, 45 90, 55 90, 55 110, 65 110,...

2 POLYGON ((90 45, 70 45, 70 35, 50 35, 50 25, 3...

3 POLYGON ((90 45, 70 45, 70 35, 50 35, 50 25, 3...

4 POLYGON ((90 45, 70 45, 70 35, 50 35, 50 25, 3...

5 POLYGON ((90 45, 70 45, 70 35, 50 35, 50 25, 3...

6 POLYGON ((50 25, 30 25, 30 15, 15 15, 15 30, 2...

7 POLYGON ((85 150, 85 170, 95 170, 95 190, 190 ...

8 POLYGON ((85 150, 85 170, 95 170, 95 190, 190 ...

9 POLYGON ((85 150, 85 170, 95 170, 95 190, 190 ...

Name: 0, dtype: object