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Fix pandas deprecation warnings #202

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merged 1 commit into from
Dec 31, 2023
Merged

Fix pandas deprecation warnings #202

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3 changes: 3 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,9 @@
__pycache__/
*.py[cod]

# IDE-specific settings
.idea/

# C extensions & files
*.so
*.c
Expand Down
22 changes: 11 additions & 11 deletions ffn/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -229,7 +229,7 @@ def _calculate(self, obj):
self.best_day = r.max()
self.worst_day = r.min()

self.total_return = obj[-1] / obj[0] - 1
self.total_return = obj.iloc[-1] / obj.iloc[0] - 1

self.cagr = calc_cagr(dp)
self.incep = self.cagr
Expand Down Expand Up @@ -305,7 +305,7 @@ def _calculate(self, obj):
# add first month
fidx = mr.index[0]
try:
self.return_table[fidx.year][fidx.month] = float(mp[0]) / dp[0] - 1
self.return_table[fidx.year][fidx.month] = float(mp.iloc[0]) / dp.iloc[0] - 1
except ZeroDivisionError:
self.return_table[fidx.year][fidx.month] = 0
# calculate the YTD values
Expand All @@ -319,7 +319,7 @@ def _calculate(self, obj):

denom = dp[: dp.index[-1] - pd.DateOffset(months=3)]
if len(denom) > 0:
self.three_month = dp[-1] / denom[-1] - 1
self.three_month = dp.iloc[-1] / denom.iloc[-1] - 1

if r.index.to_series().diff().min() < pd.Timedelta("32 days"):
if len(mr) < 4:
Expand All @@ -338,7 +338,7 @@ def _calculate(self, obj):
denom = dp[: dp.index[-1] - pd.DateOffset(months=6)]

if len(denom) > 0:
self.six_month = dp[-1] / denom[-1] - 1
self.six_month = dp.iloc[-1] / denom.iloc[-1] - 1

# Will calculate yearly figures only if the input data has at least yearly frequency or higher (e.g monthly)
# Rather < 367 days than <= 366 days in case of data taken at different hours of the days
Expand All @@ -352,7 +352,7 @@ def _calculate(self, obj):
denom = dp[: dp.index[-1] - pd.DateOffset(years=1)]

if len(denom) > 0:
self.one_year = dp[-1] / denom[-1] - 1
self.one_year = dp.iloc[-1] / denom.iloc[-1] - 1

self.yearly_mean = yr.mean()
self.yearly_vol = np.std(yr, ddof=1)
Expand Down Expand Up @@ -381,7 +381,7 @@ def _calculate(self, obj):
win = 0
for i in range(11, len(mr)):
tot += 1
if mp[i] / mp[i - 11] > 1:
if mp.iloc[i] / mp.iloc[i - 11] > 1:
win += 1
self.twelve_month_win_perc = float(win) / tot

Expand Down Expand Up @@ -1229,7 +1229,7 @@ def to_drawdown_series(prices):
drawdown = prices.copy()

# Fill NaN's with previous values
drawdown = drawdown.fillna(method="ffill")
drawdown = drawdown.ffill()

# Ignore problems with NaN's in the beginning
drawdown[np.isnan(drawdown)] = -np.Inf
Expand All @@ -1253,9 +1253,9 @@ def calc_mtd(daily_prices, monthly_prices):
else use monthly_prices
"""
if len(monthly_prices) == 1:
return daily_prices[-1] / daily_prices[0] - 1
return daily_prices.iloc[-1] / daily_prices.iloc[0] - 1
else:
return daily_prices[-1] / monthly_prices[-2] - 1
return daily_prices.iloc[-1] / monthly_prices.iloc[-2] - 1


def calc_ytd(daily_prices, yearly_prices):
Expand All @@ -1265,9 +1265,9 @@ def calc_ytd(daily_prices, yearly_prices):
else use yearly_prices
"""
if len(yearly_prices) == 1:
return daily_prices[-1] / daily_prices[0] - 1
return daily_prices.iloc[-1] / daily_prices.iloc[0] - 1
else:
return daily_prices[-1] / yearly_prices[-2] - 1
return daily_prices.iloc[-1] / yearly_prices.iloc[-2] - 1


def calc_max_drawdown(prices):
Expand Down