The table below shows a small data set in which each instance is described by three features. The k-means clustering algorithm is to be applied to this data set with k = 2 and using Euclidean distance. The initial centroids for the two clusters C1 and C2 are c1 = (0.4; 0.3; 0.2) and c2 = (0.7; 0.8; 0.7).

d1        d2       d3        dist(c1)     dist(c2)

0.392   1.258   0.666   1.065356   0.552977

0.251   1.781   1.495   1.972964   1.340144

0.823   0.042   1.254   1.164650   0.946894

0.917   0.961   0.055   0.851607   0.699310

0.736   1.694   0.686   1.514044   0.894834

1.204   0.605   0.351   0.873065   0.643306

0.778   0.436   0.220   0.402219   0.607437

1.075   1.199   0.141   1.125747   0.782500

0.854   0.654   0.771   0.810847   0.223770

Assign the data points to the appropriate clusters and calculate the new cluster centroids. What is the d1 coordinate of the centroid of the first cluster?