How to perform row wise if and mathematical operations in pandas dataframe

Question

Input Data:

Period   Invoice_No   Amount      Date
Mar-19    123         5000.00     12-02-2019
Mar-19    124         5000.00     13-02-2019
Mar-19    125         7000.00     13-02-2019
Mar-19    126         5000.00     19-02-2019
Mar-19    127         5000.00     25-02-2019
Mar-19    128         5000.00     27-02-2019

So basically want to check if first row amount (5000.00) is equal to second row amount; then perform a date difference function (13-02-2019 "-" 12-02-2019) and if difference is less than "5 days" then the following is the output. If difference is more than 5 days exclude from the output (Line number 4)

Period   Invoice_No   Amount      Date
Mar-19    123         5000.00     12-02-2019
Mar-19    124         5000.00     13-02-2019
Mar-19    127         5000.00     25-02-2019
Mar-19    128         5000.00     27-02-2019

Answer 1

You can shift the date to calculate the time delta between the rows. After I filter for the conditions you defined.

df['Date_diff'] = df['Date'].shift(-1)
df['Date_diff'] = df.apply(lambda x: pd.Timedelta(x['Date_diff'] - x['Date']),axis=1)

mask = (df['Amount'] == df['Amount'].shift(-1)) & (df['Date_diff'] < pd.Timedelta('5 days'))
mask2 = (df['Amount'] == df['Amount'].shift(1)) & (df['Date_diff'].shift(1) < pd.Timedelta('5 days'))

print(df[mask | mask2].drop('Date_diff', axis=1))

   Period  Invoice_No  Amount       Date
0  Feb-19         123  5000.0 2019-02-12
1  Feb-19         123  5000.0 2019-02-13

Answer 2

IICU:

df.sort_values(by=['Period','Date'], inplace=True)#Sortby Date
df['Date']=pd.to_datetime(df['Date'])
df['days']=df['Date'].diff().dt.days#Find days difference
df['Amountdiff']=df['Amount'].diff()#Find amount difference
df.fillna(0, inplace=True)#Fill any NaN/NaT
df2=df[df.Amountdiff==0]
df2.iloc[:,:4:]

Outcome