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wea_ondara
2020-01-27 11:58:19 +01:00
parent d2057842a7
commit da8896eadd
2 changed files with 64 additions and 7 deletions
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44
votes.py
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@@ -9,7 +9,7 @@ from datetime import timedelta
from dateutil.relativedelta import relativedelta
from common import calc_intervals, printnoln, rprint, DAYS_NEW_USER
from loader import load, dmt, cms
from loader import load, dmt, cms, readVotes
from sentiments import readtoxleveltxt
colors = ['red', 'green', 'blue', 'orange', 'deeppink']
@@ -51,8 +51,8 @@ def main(folder, intervl):
# filter nan entries
for i in range(len(datasingle)):
if len(datasingle[i]) == 0:
datasingle = float("nan")
if len(datasingle[i]) == 0:
datasingle[i] = float("nan")
if len(scoresingle[i]) == 0:
scoresingle[i] = float("nan")
print("Plotting ...")
@@ -79,14 +79,44 @@ def main(folder, intervl):
va = "bottom"
else:
va = "top"
ax.text(intervals[i][0], data[i], ("n=" if i == 0 else "") + str(len(datasingle[i])), ha="center", va=va)
plt.title("Average sentiments for new users")
ax.text(intervals[i][0], data[i], ("n=" if i == 0 else "") + (str(len(datasingle[i])) if str(datasingle[i]) != "nan" else ""), ha="center", va=va)
plt.title("Average sentiments and score for new users")
plt.xticks(rotation=90)
ax.set_xlabel("months")
ax.set_ylabel("sentiment")
ax.set_ylabel("score (votes)")
ax2.set_ylabel("score (votes)")
plt.legend(l1 + l2, [l.get_label() for l in l1 + l2], loc="upper right")
outfile = outputdir + "/average_sentiments-i" + str(intervl) + ".png"
outfile = outputdir + "/average_votes-i" + str(intervl) + ".png"
plt.savefig(outfile, bbox_inches='tight')
plt.close(fig)
# votes over time
votes = readVotes(folder)
fig = plt.figure(figsize=(16, 12))
ivs = [(datetime.fromisoformat("2010-01-01T00:00:00"), datetime.fromisoformat(str(y) + "-01-01T00:00:00")) for y in range(2011, 2020)]
for interval in ivs:
print(interval[0].strftime("%d-%m-%Y") + " to " + interval[1].strftime("%d-%m-%Y"))
ivvotes = dmt(votes).filter(lambda v: interval[0] <= v['CreationDate'] < interval[1]).getresults()
scores = []
for (option_date_from, option_date_to) in intervals:
if option_date_to > interval[1]:
continue
intervalposts = dmt(posts).filter(lambda p: option_date_from <= p['CreationDate'] < option_date_to
and firstcontrib[p['OwnerUserId']] + timedelta(days=DAYS_NEW_USER) <= p['CreationDate']).getresults()
intervalpostsids = set(dmt(intervalposts).map(lambda p: p['Id']).getresults())
intervalvotes = dmt(ivvotes).filter(lambda v: v['PostId'] in intervalpostsids).getresults()
intervalscore = sum(dmt(intervalvotes).map(lambda v: 1 if v['VoteTypeId'] == "2" else (-1 if v['VoteTypeId'] == "3" else 0)).getresults())
intervalscore = intervalscore / len(intervalpostsids) if len(intervalpostsids) != 0 else float("nan")
scores.append(((option_date_from, option_date_to), intervalscore))
# if all(str(score) == "nan" for iv, score in scores)
# continue
plt.plot([iv[0] for iv, score in scores], [score for iv, score in scores], label=str(interval[0].year) + " - " + str(interval[1].year))
plt.title("Average score for new users over time")
plt.xlabel("months")
plt.ylabel("score")
plt.legend(loc="upper right")
plt.grid(True)
outfile = outputdir + "/average_votes_over_time-i" + str(intervl) + ".png"
plt.savefig(outfile, bbox_inches='tight')
plt.close(fig)