Calculate nfl win and loss streak based on team and win/loss column

Question

I have an Excel spreadsheet that calculates the winning/losing streak of an NFL dataset using the Team and Win/Loss columns, and I'd like to put this into a panda dataframe as part of my automation project (just a hobby). Here's a sample of the data in pandas:

import pandas as pd    
df = pd.DataFrame({'DB Date': {0: 20190905,
      1: 20190905,
      2: 20190915,
      3: 20190915,
      4: 20190922,
      5: 20190923},
     'Week': {0: 1, 1: 1, 2: 2, 3: 2, 4: 3, 5: 3},
     'Team': {0: 'Bears',
      1: 'Packers',
      2: 'Bears',
      3: 'Packers',
      4: 'Packers',
      5: 'Bears'},
     'Opponent': {0: 'Packers',
      1: 'Bears',
      2: 'Broncos',
      3: 'Vikings',
      4: 'Broncos',
      5: 'Redskins'},
     'Home/Away': {0: 'home',
      1: 'away',
      2: 'away',
      3: 'home',
      4: 'home',
      5: 'away'},
     'Team Score': {0: 3, 1: 10, 2: 16, 3: 21, 4: 27, 5: 31},
     'Opp Score': {0: 10, 1: 3, 2: 14, 3: 16, 4: 16, 5: 15},
     'Win/Loss': {0: 'Loss', 1: 'Win', 2: 'Win', 3: 'Win', 4: 'Win', 5: 'Win'}})

I'm trying to add a new column that calculates the winning/losing streak to this dataframe. Here's what I have from my Excel file:

DB Date     Week    Team    Opponent    Team Score  Opp Score   Win/Loss
20190905    1       Bears   Packers        3           10       L1
20190905    1       Packers Bears          10          3        W1
20190915    2       Bears   Broncos        16          14       W1
20190915    2       Packers Vikings        21          16       W2
20190922    3       Packers Broncos        27          16       W3
20190923    3       Bears   Redskins       31          15       W2
20190926    4       Packers Eagles         27          34       L1
20190929    4       Bears   Vikings        16          6        W3
20191006    5       Packers Cowboys        34          24       W1
20191006    5       Bears   Raiders        21          24       L1

As a total beginner to Python, I have no clue how to create a function that will create this "Win Streak" column. I'd greatly appreciate any help with this!

Edit:

{'DB Date': {0: 20190905,
  1: 20190905,
  2: 20190915,
  3: 20190915,
  4: 20190922,
  5: 20190923,
  6: 20190926,
  7: 20190929,
  8: 20191006,
  9: 20191006,
  10: 20191014,
  11: 20191020,
  12: 20191020},
 'Week': {0: 1,
  1: 1,
  2: 2,
  3: 2,
  4: 3,
  5: 3,
  6: 4,
  7: 4,
  8: 5,
  9: 5,
  10: 6,
  11: 7,
  12: 7},
 'Team': {0: 'Bears',
  1: 'Packers',
  2: 'Bears',
  3: 'Packers',
  4: 'Packers',
  5: 'Bears',
  6: 'Packers',
  7: 'Bears',
  8: 'Packers',
  9: 'Bears',
  10: 'Packers',
  11: 'Bears',
  12: 'Packers'},
 'Opponent': {0: 'Packers',
  1: 'Bears',
  2: 'Broncos',
  3: 'Vikings',
  4: 'Broncos',
  5: 'Redskins',
  6: 'Eagles',
  7: 'Vikings',
  8: 'Cowboys',
  9: 'Raiders',
  10: 'Lions',
  11: 'Saints',
  12: 'Raiders'},
 'Home/Away': {0: 'home',
  1: 'away',
  2: 'away',
  3: 'home',
  4: 'home',
  5: 'away',
  6: 'home',
  7: 'home',
  8: 'away',
  9: 'neutral',
  10: 'home',
  11: 'home',
  12: 'home'},
 'Team Score': {0: 3,
  1: 10,
  2: 16,
  3: 21,
  4: 27,
  5: 31,
  6: 27,
  7: 16,
  8: 34,
  9: 21,
  10: 23,
  11: 25,
  12: 42},
 'Opp Score': {0: 10,
  1: 3,
  2: 14,
  3: 16,
  4: 16,
  5: 15,
  6: 34,
  7: 6,
  8: 24,
  9: 24,
  10: 22,
  11: 36,
  12: 24},
 'Win/Loss': {0: 'Loss',
  1: 'Win',
  2: 'Win',
  3: 'Win',
  4: 'Win',
  5: 'Win',
  6: 'Loss',
  7: 'Win',
  8: 'Win',
  9: 'Loss',
  10: 'Win',
  11: 'Loss',
  12: 'Win'}}

Answer 1

Please try this:

import numpy as np
import pandas as pd
pd.set_option('mode.chained_assignment', None)

def make_streak(S1):
    ''' This function takes the values of Win/Loss column as input and returns a list of streak values
    eg: input list : ['Loss', 'Win', 'Win', 'Win', 'Loss', 'Loss']
    output list : ['L1', 'W1', 'W2', 'W3', 'L1', 'L2'] '''
    S2 = []
    for i in range(len(S1)):
        if i==0:
            S2.append(S1[i][0]+'1');continue
        if S1[i] != S1[i-1]:
            S2.append(S1[i][0]+'1')
        if S1[i] == S1[i-1]:
            S2.append(S1[i][0]+str(int(S2[-1][-1])+1))
    return S2

def create_col(row):
    ''' This function takes every row of df as input, and returns the value for the new column:'Win/Loss Streak'(to be created)'''
    df_temp = df[(df['Team'] == row['Team'])] #Create a temporary dataframe with passed in row's team name
    df_temp['Streak'] = make_streak(df_temp['Win/Loss'].tolist())
    return (df_temp[ df_temp['row_num'] == row['row_num']]['Streak'].values[0]) #Return df_temp's last column value which matches passed in row's row number

df['row_num'] = np.arange(1,len(df)+1) #Creates a column 'row_num' to identify the rows uniquely
df['Win Streak'] = df.apply(create_col,axis=1) #Call create_col function and create 'Win Streak' column
df.drop(columns = 'row_num', inplace = True) #Drop the column 'row_num'
df