forked from wireservice/csvkit
/
csvstat.py
230 lines (175 loc) · 7.92 KB
/
csvstat.py
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#!/usr/bin/env python
import datetime
from types import NoneType
import math
from csvkit import table
from csvkit.cli import CSVKitUtility
from heapq import nlargest
from operator import itemgetter
MAX_UNIQUE = 5
MAX_FREQ = 5
OPERATIONS =('min', 'max', 'sum', 'mean', 'median', 'stdev', 'nulls', 'unique', 'freq', 'len')
class CSVStat(CSVKitUtility):
description = 'Print descriptive statistics for each column in a CSV file.'
override_flags = ['l']
def add_arguments(self):
self.argparser.add_argument('-y', '--snifflimit', dest='snifflimit', type=int,
help='Limit CSV dialect sniffing to the specified number of bytes. Specify "0" to disable sniffing entirely.')
self.argparser.add_argument('-c', '--columns', dest='columns',
help='A comma separated list of column indices or names to be examined. Defaults to all columns.')
self.argparser.add_argument('--max', dest='max_only', action='store_true',
help='Only output max.')
self.argparser.add_argument('--min', dest='min_only', action='store_true',
help='Only output min.')
self.argparser.add_argument('--sum', dest='sum_only', action='store_true',
help='Only output sum.')
self.argparser.add_argument('--mean', dest='mean_only', action='store_true',
help='Only output mean.')
self.argparser.add_argument('--median', dest='median_only', action='store_true',
help='Only output median.')
self.argparser.add_argument('--stdev', dest='stdev_only', action='store_true',
help='Only output standard deviation.')
self.argparser.add_argument('--nulls', dest='nulls_only', action='store_true',
help='Only output whether column contains nulls.')
self.argparser.add_argument('--unique', dest='unique_only', action='store_true',
help='Only output unique values.')
self.argparser.add_argument('--freq', dest='freq_only', action='store_true',
help='Only output frequent values.')
self.argparser.add_argument('--len', dest='len_only', action='store_true',
help='Only output max value length.')
def main(self):
tab = table.Table.from_csv(
self.args.file,
snifflimit=self.args.snifflimit,
column_ids=self.args.columns,
zero_based=self.args.zero_based,
no_header_row=self.args.no_header_row,
**self.reader_kwargs
)
operations = [op for op in OPERATIONS if getattr(self.args, op + '_only')]
if len(operations) > 1:
self.argparser.error('Only one statistic argument may be specified (mean, median, etc).')
for c in tab:
values = sorted(filter(lambda i: i is not None, c))
stats = {}
# Output a single stat
if len(operations) == 1:
op = operations[0]
stat = getattr(self, 'get_%s' % op)(c, values, {})
# Formatting
if op == 'unique':
stat = len(stat)
elif op == 'freq':
stat = ', '.join([(u'"%s": %s' % (unicode(k), count)).encode('utf-8') for k, count in stat])
stat = '{ %s }' % stat
if len(tab) == 1:
self.output_file.write(unicode(stat))
else:
self.output_file.write(u'%3i. %s: %s\n' % (c.order + 1, c.name, stat))
# Output all stats
else:
for op in OPERATIONS:
stats[op] = getattr(self, 'get_%s' % op)(c, values, stats)
self.output_file.write((u'%3i. %s\n' % (c.order + 1, c.name)).encode('utf-8'))
if c.type == None:
self.output_file.write(u'\tEmpty column\n')
continue
self.output_file.write(u'\t%s\n' % c.type)
self.output_file.write(u'\tNulls: %s\n' % stats['nulls'])
if len(stats['unique']) <= MAX_UNIQUE and c.type is not bool:
uniques = [unicode(u) for u in list(stats['unique'])]
self.output_file.write((u'\tValues: %s\n' % u', '.join(uniques)).encode('utf-8'))
else:
if c.type not in [unicode, bool]:
self.output_file.write(u'\tMin: %s\n' % stats['min'])
self.output_file.write(u'\tMax: %s\n' % stats['max'])
if c.type in [int, float]:
self.output_file.write(u'\tSum: %s\n' % stats['sum'])
self.output_file.write(u'\tMean: %s\n' % stats['mean'])
self.output_file.write(u'\tMedian: %s\n' % stats['median'])
self.output_file.write(u'\tStandard Deviation: %s\n' % stats['stdev'])
self.output_file.write(u'\tUnique values: %i\n' % len(stats['unique']))
if len(stats['unique']) != len(values):
self.output_file.write(u'\t%i most frequent values:\n' % MAX_FREQ)
for value, count in stats['freq']:
self.output_file.write((u'\t\t%s:\t%s\n' % (unicode(value), count)).encode('utf-8'))
if c.type == unicode:
self.output_file.write(u'\tMax length: %i\n' % stats['len'])
if not operations:
self.output_file.write(u'\n')
self.output_file.write(u'Row count: %s\n' % tab.count_rows())
def get_min(self, c, values, stats):
if c.type == NoneType:
return None
v = min(values)
if v in [datetime.datetime, datetime.date, datetime.time]:
return v.isoformat()
return v
def get_max(self, c, values, stats):
if c.type == NoneType:
return None
v = max(values)
if v in [datetime.datetime, datetime.date, datetime.time]:
return v.isoformat()
return v
def get_sum(self, c, values, stats):
if c.type not in [int, float]:
return None
return sum(values)
def get_mean(self, c, values, stats):
if c.type not in [int, float]:
return None
if 'sum' not in stats:
stats['sum'] = self.get_sum(c, values, stats)
return float(stats['sum']) / len(values)
def get_median(self, c, values, stats):
if c.type not in [int, float]:
return None
return median(values)
def get_stdev(self, c, values, stats):
if c.type not in [int, float]:
return None
if 'mean' not in stats:
stats['mean'] = self.get_mean(c, values, stats)
return math.sqrt(sum(math.pow(v - stats['mean'], 2) for v in values) / len(values))
def get_nulls(self, c, values, stats):
return c.has_nulls()
def get_unique(self, c, values, stats):
return set(values)
def get_freq(self, c, values, stats):
return freq(values)
def get_len(self, c, values, stats):
if c.type != unicode:
return None
return c.max_length()
def median(l):
"""
Compute the median of a list.
"""
length = len(l)
if len(l) % 2 == 1:
return l[((length + 1) / 2) - 1]
else:
a = l[(length / 2) - 1]
b = l[length / 2]
return (float(a + b)) / 2
def freq(l, n=MAX_FREQ):
"""
Count the number of times each value occurs in a column.
"""
count = {}
for x in l:
s = unicode(x)
if count.has_key(s):
count[s] += 1
else:
count[s] = 1
# This will iterate through dictionary, return N highest
# values as (key, value) tuples.
top = nlargest(n, count.iteritems(), itemgetter(1))
return top
def launch_new_instance():
utility = CSVStat()
utility.main()
if __name__ == "__main__":
launch_new_instance()