Make row 'Total' be the last row in pyspark dataframe

I have this dataframe

Column A	Balance	Paid Amount	Id
Total	1000	10000	null
1211	0	5000	1
1211	1000	5000	2

This code I tried for that:

df = (df.withColumn("Id", monotonically_increasing_id()+1)
           )

ANd when I try this to get my desire output:

from pyspark.sql.window import Window as W
from pyspark.sql import functions as F

df1 = df.withColumn("Id", F.monotonically_increasing_id()+1)
windowSpec = W.orderBy("Id")
df1 = df1.withColumn("Id", F.row_number().over(windowSpec)).show()

This is the df I received:

Column A	Balance	Paid Amount	Id
Total	1400	1100	null
1211	800	500	1
1211	600	600	2

This is the df desire output:

Column A	Balance	Paid Amount	Id
1211	800	500	1
1211	600	600	2
Total	1400	1100	3

EDIT:

I tried the below answers from this post but I still got the same error. The values of Balance & Paid Amount is different from the 1st dataframe.

df1:

Column A	Balance	Paid Amount	Id
Total	2000	1500	null
1211	800	500	1
1211	600	600	2
1211	400	300	3
1211	200	100	4

codes I have tried:

from pyspark.sql import functions as F

total_row = df.filter(F.col("Column A") == "Total")
other_rows = df.filter(F.col("Column A") != "Total")

final_df = other_rows.union(total_row)
final_df.show()


from pyspark.sql import functions as F
from pyspark.sql.window import Window as W

df1 = df1.withColumn("Flag", F.when(F.col("Column A") == "Total", 1).otherwise(0))
windowSpec = W.orderBy("Flag", "Column A")
df1 = df1.withColumn("Id", F.row_number().over(windowSpec))
df1 = df1.drop("Flag")
df1.show()

same output:

Column A	Balance	Paid Amount	Id
1211	800	500	1
1211	800	500	2
1211	800	500	3
1211	200	100	4
Total	2000	1500	5

Correct result of Total for two columns, however, the values have changed.

Solution

Here is the sample data frame:

Column A	Balance	Paid Amount	Id
Total	1400	1100	NULL
1211	800	500	1
1211	600	600	2

You can use below code to get your required output data frame:

from pyspark.sql import functions as F
from pyspark.sql.window import Window as W

df1 = df1.withColumn("Flag", F.when(F.col("Column A") == "Total", 1).otherwise(0))
windowSpec = W.orderBy("Flag", "Column A")
df1 = df1.withColumn("Id", F.row_number().over(windowSpec))
df1 = df1.drop("Flag")
df1.show()

You will get the below dataframe as output:

Column A	Balance	Paid Amount	Id
1211	800	500	1
1211	600	600	2
Total	1400	1100	3