[FIXED] get unique labels of a list and convert to dataframe for plotting

Issue

i have a set of lists and i need the labels to be a single column in a dataframe and the values in label that is not in the value(after the merge) should be 0.

label = [0, 2, 1, 3, 4, 9, 8, 24, 86, 5] value = [103, 16, 10, 9, 5, 4, 4, 3, 3, 3]

label1 = [0, 2, 3, 1, 9, 15, 4, 6, 5, 23] value1 = [73, 14, 8, 7, 3, 3, 3, 2, 2, 2]

label2 = [0, 2, 1, 3, 9, 6, 10, 15, 4, 114] value2 = [48, 11, 7, 6, 3, 2, 2, 2, 2, 1]

i need to merge all of these to look like this:

label = [0, 2, 1, 3, 4, 9, 8, 15, 23, 10, 24, 86, 5, 114]
value = [103, 16, 10, 9, 5, 4, 4, 0, 0, 0, 3, 3, 3, 0]
value1 = [73, 14, 7, 8, 0, 3, 0, 3, 2, 0, 0, 0, 2, 0]
value2 = [48, 11, 7, 6, 2, 3, 0, 2, 0, 2, 0, 0, 0, 1]

the reason for this is so that i can plot the data on a seaborn scatterplot/pairplot but i do not mind if there is a way to plot the first sets of data on scatterplot/pairplot

Solution

one way to do this is to use outer merge, which will merge columns of dataframe based on the column you choose. Below is the code. First convert the label-value pairs into dataframes, then merge the 3 dataframes. Finally, change the column names to what you want to see...

## Your data
label = [0, 2, 1, 3, 4, 9, 8, 24, 86, 5] 
value = [103, 16, 10, 9, 5, 4, 4, 3, 3, 3]
label1 = [0, 2, 3, 1, 9, 15, 4, 6, 5, 23] 
value1 = [73, 14, 8, 7, 3, 3, 3, 2, 2, 2]
label2 = [0, 2, 1, 3, 9, 6, 10, 15, 4, 114] 
value2 = [48, 11, 7, 6, 3, 2, 2, 2, 2, 1]

## Conver each list into dataframe
df=pd.DataFrame({'label':label, 'value':value})
df1=pd.DataFrame({'label':label1, 'value':value1})
df2=pd.DataFrame({'label':label2, 'value':value2})

## Merge the dataframes on label column
dfresult = pd.merge(df, df1, how="outer", on='label')
dfresult = pd.merge(dfresult, df2, how="outer", on='label').fillna(0)

## Rename columns and convert data to int
dfresult.rename(columns={'value':'value2', 'value_x':'value', 'value_y':'value1'}, inplace=True)
dfresult=dfresult.astype(int)
dfresult

Output

    label   value   value1  value2
0   0   103 73  48
1   2   16  14  11
2   1   10  7   7
3   3   9   8   6
4   4   5   3   2
5   9   4   3   3
6   8   4   0   0
7   24  3   0   0
8   86  3   0   0
9   5   3   2   0
10  15  0   3   2
11  6   0   2   2
12  23  0   2   0
13  10  0   0   2
14  114 0   0   1

Answered By - Redox