Seasonality Monthly v2.0

//version=6
indicator("Seasonality Monthly v2.0", overlay=false)

if not (timeframe.ismonthly or timeframe.isdaily)
alert("Switch to Daily or Monthly timeframe", alert.freq_once_per_bar)

// Input Settings
i_year_start = input(2000, "Start Year")
i_text_size = input.string(size.auto, "Text Size", [size.auto, size.tiny, size.small, size.normal, size.large, size.huge])

// Function for calculating statistics
f_array_stats(array_) =>
count_pos_ = 0
count_neg_ = 0
count_ = 0
sum_ = 0.0
if not na(array_) and array.size(array_) > 0
for i_ = 0 to array.size(array_) - 1
elem_ = array.get(array_, i_)
if not na(elem_)
sum_ += elem_
count_ += 1
count_pos_ += elem_ > 0 ? 1 : 0
count_neg_ += elem_ < 0 ? 1 : 0
avg_ = count_ > 0 ? sum_ / count_ : 0.0
[sum_, avg_, count_, count_pos_, count_neg_]

// Request historical data
year_ = request.security(syminfo.tickerid, "M", year(time_close), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)
month_ = request.security(syminfo.tickerid, "M", month(time_close), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)
chg_pct_ = request.security(syminfo.tickerid, "M", nz(close / close[1] - 1), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)

// Initialize variables
var year_start_ = math.max(year_, i_year_start)
var no_years_ = year(timenow) - year_start_ + 1
var matrix<float> data_ = matrix.new<float>(no_years_, 13, na)
var table table_ = na
var text_color_ = color.white
var bg_color_ = color.gray

if year_ >= year_start_
cur_val_ = nz(matrix.get(data_, year_ - year_start_, month_ - 1))
matrix.set(data_, year_ - year_start_, month_ - 1, cur_val_ + chg_pct_)

if barstate.islast
table_ := table.new(position.middle_center, 13, no_years_ + 7, border_width = 1)
table.cell(table_, 0, 0, str.format("Seasonality Monthly Performance - {0}:{1}", syminfo.prefix, syminfo.ticker), text_color = text_color_, bgcolor = color.blue, text_size = i_text_size)
table.merge_cells(table_, 0, 0, 12, 0)
row = 1

// Header row
months_ ="Year", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"
for col = 0 to 12
table.cell(table_, col, row, months_[col], text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)

// Data rows
for row_ = 0 to no_years_ - 1
table.cell(table_, 0, 2 + row_, str.tostring(row_ + year_start_), text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)
for col_ = 0 to 11
val_ = nz(matrix.get(data_, row_, col_), 0.0)
val_color_ = val_ > 0.0 ? color.green : val_ < 0.0 ? color.red : color.gray
table.cell(table_, col_ + 1, 2 + row_, str.format("{0,number,###.##%}", val_), bgcolor = color.new(val_color_, 80), text_color = val_color_, text_size = i_text_size)

// Aggregates
row_ = no_years_ + 2
labels = "AVG", "SUM", "+ive", "WR"
for i = 0 to 3
table.cell(table_, 0, row_ + i, labels, text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)

for col_ = 0 to 11
arr_ = matrix.col(data_, col_)
[sum_, avg_, count_, count_pos_, count_neg_] = f_array_stats(arr_)
val_color_ = sum_ > 0 ? color.green : sum_ < 0 ? color.red : color.gray

table.cell(table_, col_ + 1, row_, str.format("{0,number,###.##%}", avg_), bgcolor = color.new(val_color_, 50), text_color = val_color_, text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 1, str.format("{0,number,###.##%}", sum_), bgcolor = color.new(val_color_, 50), text_color = val_color_, text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 2, str.format("{0}/{1}", count_pos_, count_), bgcolor = color.new(val_color_, 50), text_color = color.new(color.white, 50), text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 3, str.format("{0,number,#.##%}", count_pos_ / count_), bgcolor = color.new(val_color_, 50), text_color = color.new(color.white, 50), text_size = i_text_size)