- Rdatasets (2264)
- UC Irvine Machine Learning Repository (663)
- OpenIntro Data Sets (284)
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# Returns NaN. | |
function nan() { | |
return "+NaN" + 0 | |
} | |
# Returns the binomial coefficient. | |
# It works, at least, when either n or k is a non-negative integer. | |
function binom(n, k, tmp) { | |
if (n == k || k == 0) { | |
return 1 |
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=LAMBDA( | |
LET( | |
upRange, INDIRECT(ADDRESS(1, COLUMN()) & ":" & ADDRESS(ROW() - 1, COLUMN())), | |
lastNumber, LOOKUP(2, 1 / ISNUMBER(upRange), upRange), | |
IF(ISNUMBER(lastNumber), | |
lastNumber + 1, | |
"" | |
) | |
) | |
) |
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(* cf. https://mathematica.stackexchange.com/a/278798 *) | |
makeImage[g_] := Block[{$ImageResolution = 300}, | |
Export[CloudObject["output.png"], g, "PNG"]; | |
Show[g] | |
]; |
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SOURCES := $(wildcard *.tex) | |
DOCUMENTS := $(SOURCES:.tex=.pdf) | |
CLEANFILES := \ | |
$(foreach doc,$(DOCUMENTS),"$(doc)") \ | |
$(foreach doc,$(SOURCES:.tex=.aux),"$(doc)") \ | |
$(foreach doc,$(SOURCES:.tex=.log),"$(doc)") | |
all: $(DOCUMENTS) | |
clean: |
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def plot_data(data, *, figsize=None, columns=None, col_wrap=5, cat_threshold=5): | |
import matplotlib.pyplt as plt | |
import seaborn as sns | |
import pandas as pd | |
if not columns: | |
columns = data.columns | |
n_rows = len(columns) // col_wrap + 1 | |
if not figsize: | |
figsize = (col_wrap * 4, n_rows * 3) |
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#!/bin/bash | |
# | |
# Usage: | |
# ./x [check] | |
# [coverage|gprof|valgrind [<valgrind options>]|helgrind|drd|sanitize] | |
# [form|vorm|tform|tvorm|parform|parvorm] | |
# [args...] | |
# | |
# valgrind-options = | |
# [--leak-check=<no|summary|yes|full>] |
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* Example: | |
* form -D M=10 -D N=15 test11.frm | |
Symbol x1,...,x`M'; | |
Local F = (x1+...+x`M')^`N'; | |
.end |
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#!/bin/sh | |
# | |
# @file auto-cherry-pick.sh | |
# | |
# Usage: | |
# auto-cherry-pick.sh ref1...ref2: | |
# | |
set -eu | |
output=auto-cherry-pick.log |
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