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Hi,
Just tried the package and I get this warning.
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of series[i:j] with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g. series[i] lookups. To retain the old behavior, use series.iloc[i:j]. To get the future behavior, use series.loc[i:j].
return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of series[i:j] with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g. series[i] lookups. To retain the old behavior, use series.iloc[i:j]. To get the future behavior, use series.loc[i:j].
return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of series[i:j] with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g. series[i] lookups. To retain the old behavior, use series.iloc[i:j]. To get the future behavior, use series.loc[i:j].
return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:374: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:435: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of series[i:j] with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g. series[i] lookups. To retain the old behavior, use series.iloc[i:j]. To get the future behavior, use series.loc[i:j].
return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:291: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:336: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
The text was updated successfully, but these errors were encountered:
Hi,
Just tried the package and I get this warning.
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of
series[i:j]
with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g.series[i]
lookups. To retain the old behavior, useseries.iloc[i:j]
. To get the future behavior, useseries.loc[i:j]
.return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of
series[i:j]
with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g.series[i]
lookups. To retain the old behavior, useseries.iloc[i:j]
. To get the future behavior, useseries.loc[i:j]
.return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of
series[i:j]
with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g.series[i]
lookups. To retain the old behavior, useseries.iloc[i:j]
. To get the future behavior, useseries.loc[i:j]
.return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:374: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:435: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:469: FutureWarning: The behavior of
series[i:j]
with an integer-dtype index is deprecated. In a future version, this will be treated as label-based indexing, consistent with e.g.series[i]
lookups. To retain the old behavior, useseries.iloc[i:j]
. To get the future behavior, useseries.loc[i:j]
.return property[-years:].sum() / years
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:291: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
/usr/local/lib/python3.9/dist-packages/valinvest/fundamentals.py:336: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.
stmt[stmt["header"] == "net_income"].groupby(
The text was updated successfully, but these errors were encountered: