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Updated basic_project_stats to Python 3 #2

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Updated basic_project_stats to Python 3 #2

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31 changes: 16 additions & 15 deletions basic_project_stats.py
100644 → 100755
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
#Updated to Python 3.8.3 (Feb 23, 2023)
#Python 2.7.9 (default, Apr 5 2015, 22:21:35)
import sys

Expand All @@ -7,9 +8,9 @@
classfile_in = sys.argv[1]
except:
#classfile_in = 'data/2e3d12a2-56ca-4d1f-930a-9ecc7fd39885.csv'
print "\nUsage: "+sys.argv[0]+" classifications_infile"
print " classifications_infile is a Zooniverse (Panoptes) classifications data export CSV."
print "\nAll output will be to stdout (about a paragraph worth).\n"
print("\nUsage: "+sys.argv[0]+" classifications_infile")
print(" classifications_infile is a Zooniverse (Panoptes) classifications data export CSV.")
print("\nAll output will be to stdout (about a paragraph worth).\n")
sys.exit(0)


Expand Down Expand Up @@ -54,8 +55,8 @@


# Print out the input parameters just as a sanity check
print "Computing project stats using:"
print " infile:",classfile_in
print("Computing project stats using:")
print(" infile:",classfile_in)



Expand Down Expand Up @@ -117,7 +118,7 @@ def gini(list_of_values):
# Begin the main stuff


print "Reading classifications from "+classfile_in
print("Reading classifications from "+classfile_in)

classifications = pd.read_csv(classfile_in)

Expand Down Expand Up @@ -174,7 +175,7 @@ def gini(list_of_values):
# e.g. whether they're also your most prolific Talk users
nclass_byuser = by_user.created_at.aggregate('count')
nclass_byuser_ranked = nclass_byuser.copy()
nclass_byuser_ranked.sort(ascending=False)
nclass_byuser_ranked.sort_values(ascending=False,inplace=True)

# very basic stats
nclass_med = np.median(nclass_byuser)
Expand All @@ -183,14 +184,14 @@ def gini(list_of_values):
# Gini coefficient - see the comments above the gini() function for more notes
nclass_gini = gini(nclass_byuser)

print "\nOverall:\n\n",n_class_tot,"classifications of",n_subj_tot,"subjects by",n_users_tot,"classifiers,"
print n_reg,"registered and",n_unreg,"unregistered.\n"
print "That's %.2f classifications per subject on average (median = %.1f)." % (subj_class_mean, subj_class_med)
print "The most classified subject has ",subj_class_max,"classifications; the least-classified subject has",subj_class_min,".\n"
print "Median number of classifications per user:",nclass_med
print "Mean number of classifications per user: %.2f" % nclass_mean
print "\nTop 10 most prolific classifiers:\n",nclass_byuser_ranked.head(10)
print "\n\nGini coefficient for classifications by user: %.2f\n" % nclass_gini
print("\nOverall:\n\n",n_class_tot,"classifications of",n_subj_tot,"subjects by",n_users_tot,"classifiers,")
print(n_reg,"registered and",n_unreg,"unregistered.\n")
print("That's %.2f classifications per subject on average (median = %.1f)." % (subj_class_mean, subj_class_med))
print("The most classified subject has ",subj_class_max,"classifications; the least-classified subject has",subj_class_min,".\n")
print("Median number of classifications per user:",nclass_med)
print("Mean number of classifications per user: %.2f" % nclass_mean)
print("\nTop 10 most prolific classifiers:\n",nclass_byuser_ranked.head(10))
print("\n\nGini coefficient for classifications by user: %.2f\n" % nclass_gini)


# That's it. This program is very basic.