Show specific 1 value from column-CodePudding

I have this function written in python. I want this thing show only one value.

Here's the code

def show_data():
    
    df = pd.DataFrame(myresult, columns=['Year', 'Production (Ton)'])
    df['Max Prod'] = df['Production (Ton)'].max())

    print(df)

And of course the output is this

    Year Production (Ton)  Max Prod

0   2010           339491    366999
1   2011           366999    366999
2   2012           361986    366999
3   2013           329461    366999
4   2014           355464    366999
5   2015           344998    366999
6   2016           274317    366999
7   2017           200916    366999
8   2018           217246    366999
9   2019           119830    366999
10  2020            66640    366999

Since it has the same value, I want the output like this

    Year Production (Ton)  Max Prod

0   2010           339491    366999    
1   2011           366999    
2   2012           361986   
3   2013           329461   
4   2014           355464  
5   2015           344998   
6   2016           274317   
7   2017           200916   
8   2018           217246  
9   2019           119830   
10  2020            66640

What should I change or add to my code?

CodePudding user response：

You can use shift to generate a mask that can be used to replace duplicate consecutive values:

df.loc[df['Max Prod'] == df['Max Prod'].shift(1), 'Max Prod'] = ''

Output:

>>> df
    Year  Production (Ton) Max Prod
0   2010            339491   366999
1   2011            366999 
2   2012            361986 
3   2013            329461 
4   2014            355464 
5   2015            344998 
6   2016            274317 
7   2017            200916 
8   2018            217246 
9   2019            119830 
10  2020             66640

CodePudding user response：

You could also have the function as:

def show_data():
    df = pd.DataFrame(myresult, columns=['Year', 'Production (Ton)'])
    df['Max Prod'] = ''
    df.iloc[0, -1] = df['Production (Ton)'].max()

    print(df)

CodePudding user response：

Given what you have now:

def show_data():    
    df = pd.DataFrame(myresult, columns=['Year', 'Production (Ton)'])
    df['Max Prod'] = df['Production (Ton)'].max())
    df = df['Max Prod'].drop_duplicates()
    df = df.fillna('')
    print(df)

Output:

    Year  Production-(Ton) Max Prod
0   2010            339491   549713
1   2011            366999 
2   2012            361986 
3   2013            329461 
4   2014            355464 
5   2015            344998 
6   2016            274317 
7   2017            200916 
8   2018            217246 
9   2019            119830 
10  2020             66640