在熊猫数据框中查找第一个重复的连续条目

Question

I have a dataframe of two columns Stock and DueDate , where I need to select first row from the repeated consecutive entries based on stock column.

df:

I am expecting output like below,

Expected output:

My Approach

The approach I tried to use is to first list out what all rows repeating based on stock column by creating a new column repeated_yes and then subset the first row only if any rows are repeating more than twice.

I have used the below line of code to create new column "repeated_yes",

    ss = df.Stock.ne(df.Stock.shift())
    df['repeated_yes'] = ss.groupby(ss.cumsum()).cumcount() + 1 

so the new updated dataframe looks like this,

df_new

But I am stuck on subsetting only row number 3 and 8 inorder to attain the result. If there are any other effective approach it would be helpful.

Edited: Forgot to include the actual full question, If there are any other rows below the last row in the dataframe df it should not display any output.

Answer 1

Chain another mask created by Series.duplicated with keep=False by & for bitwise AND and filter in boolean indexing :

ss = df.Stock.ne(df.Stock.shift())
ss1 = ss.cumsum().duplicated(keep=False)

df = df[ss & ss1]