经过一些转换后，我的df看起来像这样。
date 2010-01-01 2010-01-08 2010-01-15 2010-01-22 2010-01-29 2010-02-05 2010-02-12 2010-02-19 2010-02-26 2010-03-05 ... 2020-08-28 2020-09-04 2020-09-11 2020-09-18 2020-09-25 2020-10-02 2020-10-09 2020-10-16 2020-10-23 2020-10-30
gestionnaire nom_de_produit code_isin_part classification_produit
ACTIS ASSET MANAGEMENT ALTERNA PLUS FR0010466128 Sans classification 11.29 11.49 11.51 11.44 11.37 11.29 11.29 11.35 11.38 11.51 ... 15.87 15.84 15.87 15.86 15.72 15.77 15.88 15.91 15.95 15.75
GTA FRANCE FR0010602615 Actions de pays de la zone euro 81.71 84.26 82.78 80.31 78.50 74.93 75.27 78.89 77.70 81.22 ... 127.12 124.41 126.55 126.78 122.47 125.28 127.37 127.91 127.28 120.65
RENTOBLIG FR0010698472 Obligations et/ou titres de créances libellés en euros nan 121.69 121.98 121.74 121.32 121.17 120.87 120.73 121.22 121.99 ... 158.62 158.85 158.89 159.00 157.70 158.14 159.56 159.57 160.21 159.44
FR0013180288 Obligations et/ou titres de créances libellés en euros nan nan nan nan nan nan nan nan nan nan ... 105.32 105.48 105.51 105.59 104.73 105.03 105.98 105.99 106.43 105.92
SCR OPTIMUM FR0012453348 Sans classification nan nan nan nan nan nan nan nan nan nan ... 92,562.20 92,220.46 91,434.86 91,524.37 91,542.14 91,229.36 91,226.54 91,123.66 92,072.99 91,480.94
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
TRUSTEAM FINANCE TRUSTEAM ROC EUROPE FR0011507219 Actions des pays de l'Union Européenne nan nan nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan nan nan
FR0011896430 Actions des pays de l'Union Européenne nan nan nan nan nan nan nan nan nan nan ... 197.71 191.56 193.59 197.04 194.41 199.31 201.71 203.33 197.97 190.02
FR0013281185 Actions des pays de l'Union Européenne nan nan nan nan nan nan nan nan nan nan ... 191.65 185.65 187.59 190.90 188.31 193.02 195.31 196.84 191.61 183.89
TRUSTEAM ROC FLEX FR0007018239 Sans classification 178.11 179.38 179.51 177.38 175.57 174.82 174.81 175.79 175.43 177.50 ... 227.48 228.16 228.81 228.20 226.08 227.64 230.02 230.21 230.49 227.22
TRUSTEAM ROC PME FR0010220038 Actions de pays de la zone euro 87.59 89.57 90.00 89.82 90.08 88.22 88.30 88.64 88.69 90.75 ... 181.93 183.06 186.22 186.15 178.61 182.79 187.55 184.17 185.64
我想计算日历性能和其他统计信息。为此，我这样做：
df.apply([
lambda x: pd.Series([100*x[year].iloc[-1]/x[year].iloc[0] - 100 for year in pd.date_range(start='2015', end='2021', freq='A').strftime('%Y')]),
],
axis=1)
)
没关系。
但是当我添加时：
df.apply([lambda x: pd.Series([100*x[year].iloc[-1]/x[year].iloc[0] - 100 for year in pd.date_range(start='2015', end='2021', freq='A').strftime('%Y')]),
lambda x: 100*x[-1]/x[-52]-100
],
axis=1)
)
我收到一条错误消息：
ValueError: cannot combine transform and aggregation operations
有什么想法吗？