Move data from row 1 to row 0-CodePudding

I have this function written in python. I want this thing show difference between row from production column.

Here's the code

def print_df():
    mycursor.execute("SELECT * FROM productions")
 
    myresult = mycurson.fetchall()
    myresult.sort(key=lambda x: x[0])
    
    df = pd.DataFrame(myresult, columns=['Year', 'Production (Ton)'])
    df['Dif'] = abs(df['Production (Ton)']. diff())

    print(abs(df))

And of course the output is this

    Year Production (Ton)       Dif

0   2010           339491       NaN
1   2011           366999   27508.0
2   2012           361986    5013.0
3   2013           329461   32525.0
4   2014           355464   26003.0
5   2015           344998   10466.0
6   2016           274317   70681.0
7   2017           200916   73401.0
8   2018           217246   16330.0
9   2019           119830   97416.0
10  2020            66640   53190.0

But I want the output like this

    Year Production (Ton)       Dif

0   2010           339491   27508.0    
1   2011           366999    5013.0
2   2012           361986   32525.0 
3   2013           329461   26003.0
4   2014           355464   10466.0
5   2015           344998   70681.0
6   2016           274317   73401.0
7   2017           200916   16330.0
8   2018           217246   97416.0
9   2019           119830   53190.0
10  2020            66640   66640.0

What should I change or add to my code?

CodePudding user response：

You can use a negative period input to diff to get the differences the way you want, and then fillna to fill the last value with the value from the Production column:

df['Dif'] = df['Production (Ton)'].diff(-1).fillna(df['Production (Ton)']).abs()

Output:

    Year  Production (Ton)      Dif
0   2010            339491  27508.0
1   2011            366999   5013.0
2   2012            361986  32525.0
3   2013            329461  26003.0
4   2014            355464  10466.0
5   2015            344998  70681.0
6   2016            274317  73401.0
7   2017            200916  16330.0
8   2018            217246  97416.0
9   2019            119830  53190.0
10  2020             66640  66640.0

CodePudding user response：

Use shift(-1) to shift all rows one position up.

df['Dif'] = (df['Production (Ton)'] - df['Production (Ton)'].shift(-1).fillna(0)).abs()

Notice that by setting fillna(0), you avoid the NaNs.

You can also use diff:

df['Dif'] = df['Production (Ton)'].diff().shift(-1).fillna(0).abs()