CODEWITHSUNDEEP
pythonpytorch
ziiho_
ziiho_

Reputation: 43

How to get value in order with a small average value

I've got a data frame like

x  y    cluster
0  112  4
0  113  4
1  111  4

and I'll get locations from this code:

for n in range(0,9): 
...
    location = np.array(cluseter_location )

I want to sort it out in the order of column 'cluster' with small columns 'y' means, so I tried:

for n in range(0,9):
    cluster_ = data2[data2['cluster_id']== n]

    ...

Upvotes: 0

Views: 59

Answers (1)

Akshay Sehgal
Akshay Sehgal

Reputation: 19307

Modifying your code to sort list of tuples

In your code, instead of appending the cluster_int, just append the tuple (n, cluster_int), and then later while sorting, use lambda to sort by the second value of each tuple.

for n in range(0,9):
    cluster_ = data2[data2['cluster_id']== n]

    cluster_list = cluster_['y'].tolist()
    cluster_avg = sum(cluster_list)/len(cluster_list)

    cluster_int = int(cluster_avg)

    print("cluster_id : %d" %n ,"average : %d" %cluster_int)
    lst.append((n,cluster_int))                              #<-------
    a = sorted(lst, key = lambda x:x[1])                     #<-------


print(a)                                                     #<-------

ordered_average = [average for cluster, average in a]        #<-------
ordered_clusters = [cluster for cluster, average in a]       #<-------

print(ordered_average)                                       #<-------
print(ordered_clusters)                                      #<-------

#cluster and average together
[(4,112),(8,121,(1,127),(6,139),(5,149)]

#averages sorted
[112, 121, 127, 139, 149]

#clusters sorted
[4,8,1,6,5]

Alternate way using pandas

A quicker way to do this would be directly sorting the pandas dataframe after groupby.

print(df.groupby('cluster')['y'].mean().reset_index().sort_values('y'))

Upvotes: 1

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