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Reduce Pandas deprecation warnings. #263

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Reduce Pandas deprecation warnings. #263

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52a409a
Fix df.stack future_stack warning.
Sep 18, 2024
68b7901
Reduce warnings like for iloc and future_stack.
Sep 18, 2024
51a8a7c
Fix warning.
Sep 18, 2024
a076b97
Reduce warnings.
Sep 18, 2024
375ed8b
Reduce warnings.
Sep 18, 2024
a1a924f
Changes to reduce Pandas deprecation warnings from 33000 to 1600.
Sep 18, 2024
057a7fc
Dict.iteritems deprecated in Python 3, use Dist.items instead.
Sep 18, 2024
2eec36c
Another couple .ilocs needed.
Sep 19, 2024
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Reduce warnings like for iloc and future_stack.
Jim White committed Sep 18, 2024
commit 68b7901dc2d722706ebf9031697cb453d406aac6
2 changes: 1 addition & 1 deletion src/zipline/pipeline/loaders/earnings_estimates.py
View file
Original file line number Diff line number Diff line change
@@ -702,7 +702,7 @@ def get_last_data_per_qtr(
ffill_across_cols(last_per_qtr, columns, self.name_map)
# Stack quarter and sid into the index.
stacked_last_per_qtr = last_per_qtr.stack(
[SID_FIELD_NAME, NORMALIZED_QUARTERS],
[SID_FIELD_NAME, NORMALIZED_QUARTERS], future_stack=True
)
# Set date index name for ease of reference
stacked_last_per_qtr.index.set_names(
33 changes: 17 additions & 16 deletions tests/pipeline/test_quarters_estimates.py
View file
Original file line number Diff line number Diff line change
@@ -833,28 +833,29 @@ def make_loader(cls, events, columns):
def fill_expected_out(cls, expected):
# Fill columns for 1 Q out
for raw_name in cls.columns.values():
expected[raw_name + "1"].loc[
pd.Timestamp(
"2015-01-12",
) : pd.Timestamp("2015-01-19")
expected.loc[
pd.Timestamp("2015-01-12") : pd.Timestamp("2015-01-19"),
raw_name + "1"
] = cls.events[raw_name].iloc[0]
expected[raw_name + "1"].loc[pd.Timestamp("2015-01-20") :] = cls.events[
expected.loc[pd.Timestamp("2015-01-20") :, raw_name + "1"] = cls.events[
raw_name
].iloc[1]

# Fill columns for 2 Q out
for col_name in ["estimate", "event_date"]:
expected[col_name + "2"].loc[pd.Timestamp("2015-01-20") :] = cls.events[
expected.loc[pd.Timestamp("2015-01-20") :, col_name + "2"] = cls.events[
col_name
].iloc[0]
expected[FISCAL_QUARTER_FIELD_NAME + "2"].loc[
pd.Timestamp("2015-01-12") : pd.Timestamp("2015-01-20")
expected.loc[
pd.Timestamp("2015-01-12") : pd.Timestamp("2015-01-20"),
FISCAL_QUARTER_FIELD_NAME + "2"
] = 4
expected[FISCAL_YEAR_FIELD_NAME + "2"].loc[
pd.Timestamp("2015-01-12") : pd.Timestamp("2015-01-20")
expected.loc[
pd.Timestamp("2015-01-12") : pd.Timestamp("2015-01-20"),
FISCAL_YEAR_FIELD_NAME + "2"
] = 2014
expected[FISCAL_QUARTER_FIELD_NAME + "2"].loc[pd.Timestamp("2015-01-20") :] = 1
expected[FISCAL_YEAR_FIELD_NAME + "2"].loc[pd.Timestamp("2015-01-20") :] = 2015
expected.loc[pd.Timestamp("2015-01-20") :, FISCAL_QUARTER_FIELD_NAME + "2"] = 1
expected.loc[pd.Timestamp("2015-01-20") :, FISCAL_YEAR_FIELD_NAME + "2"] = 2015
return expected


@@ -2666,7 +2667,7 @@ def make_expected_out(cls):
.set_index(SID_FIELD_NAME, append=True)
.unstack(SID_FIELD_NAME)
.reindex(cls.trading_days)
.stack(SID_FIELD_NAME, dropna=False)
.stack(SID_FIELD_NAME, future_stack=True)
)

split_adjusted_at_end_boundary = (
@@ -2733,7 +2734,7 @@ def make_expected_out(cls):
.set_index(SID_FIELD_NAME, append=True)
.unstack(SID_FIELD_NAME)
.reindex(cls.trading_days)
.stack(SID_FIELD_NAME, dropna=False)
.stack(SID_FIELD_NAME, future_stack=True)
)

split_adjusted_before_start_boundary = split_adjusted_at_start_boundary
@@ -2812,7 +2813,7 @@ def make_expected_out(cls):
.set_index(SID_FIELD_NAME, append=True)
.unstack(SID_FIELD_NAME)
.reindex(cls.trading_days)
.stack(SID_FIELD_NAME, dropna=False)
.stack(SID_FIELD_NAME, future_stack=True)
)

split_adjusted_at_end_boundary = (
@@ -2867,7 +2868,7 @@ def make_expected_out(cls):
.set_index(SID_FIELD_NAME, append=True)
.unstack(SID_FIELD_NAME)
.reindex(cls.trading_days)
.stack(SID_FIELD_NAME, dropna=False)
.stack(SID_FIELD_NAME, future_stack=True)
)

split_adjusted_before_start_boundary = split_adjusted_at_start_boundary