|
525 | 525 | "outputs": [], |
526 | 526 | "source": [ |
527 | 527 | "from sklearn.preprocessing import PolynomialFeatures\n", |
528 | | - "from rpy2.robjects.packages import importr, data\n", |
529 | | - "from rpy2.robjects import r, pandas2ri\n", |
530 | | - "pandas2ri.activate()" |
| 528 | + "from rpy2.robjects.packages import PackageData\n", |
| 529 | + "from rpy2.robjects import pandas2ri, default_converter, conversion" |
531 | 530 | ] |
532 | 531 | }, |
533 | 532 | { |
|
538 | 537 | }, |
539 | 538 | "outputs": [], |
540 | 539 | "source": [ |
541 | | - "hdm = importr('hdm')\n", |
542 | | - "blp_data = data(hdm).fetch('BLP')['BLP'][0]" |
| 540 | + "r_df = PackageData('hdm').fetch('BLP')['BLP'][0]\n", |
| 541 | + "with conversion.localconverter(default_converter + pandas2ri.converter):\n", |
| 542 | + " blp_data = conversion.rpy2py(r_df)" |
543 | 543 | ] |
544 | 544 | }, |
545 | 545 | { |
|
754 | 754 | "res = dml_pliv.summary.reset_index(drop=True)\n", |
755 | 755 | "res['z_col'] = dml_data.z_cols[0]\n", |
756 | 756 | "res['clustering'] = 'two-way'\n", |
757 | | - "res_df = res_df.append(res)" |
| 757 | + "res_df = pd.concat([res_df, res]).reset_index(drop=True)" |
758 | 758 | ] |
759 | 759 | }, |
760 | 760 | { |
|
783 | 783 | "res = dml_pliv.summary.reset_index(drop=True)\n", |
784 | 784 | "res['z_col'] = dml_data.z_cols[0]\n", |
785 | 785 | "res['clustering'] = 'one-way-product'\n", |
786 | | - "res_df = res_df.append(res)" |
| 786 | + "res_df = pd.concat([res_df, res]).reset_index(drop=True)" |
787 | 787 | ] |
788 | 788 | }, |
789 | 789 | { |
|
812 | 812 | "res = dml_pliv.summary.reset_index(drop=True)\n", |
813 | 813 | "res['z_col'] = dml_data.z_cols[0]\n", |
814 | 814 | "res['clustering'] = 'one-way-market'\n", |
815 | | - "res_df = res_df.append(res)" |
| 815 | + "res_df = pd.concat([res_df, res]).reset_index(drop=True)" |
816 | 816 | ] |
817 | 817 | }, |
818 | 818 | { |
|
866 | 866 | "res = dml_pliv.summary.reset_index(drop=True)\n", |
867 | 867 | "res['z_col'] = dml_data.z_cols[0]\n", |
868 | 868 | "res['clustering'] = 'zero-way'\n", |
869 | | - "res_df = res_df.append(res)" |
| 869 | + "res_df = pd.concat([res_df, res]).reset_index(drop=True)" |
870 | 870 | ] |
871 | 871 | }, |
872 | 872 | { |
|
988 | 988 | "provenance": [] |
989 | 989 | }, |
990 | 990 | "kernelspec": { |
991 | | - "display_name": "Python 3", |
| 991 | + "display_name": "Python 3 (ipykernel)", |
992 | 992 | "language": "python", |
993 | 993 | "name": "python3" |
994 | 994 | }, |
|
1002 | 1002 | "name": "python", |
1003 | 1003 | "nbconvert_exporter": "python", |
1004 | 1004 | "pygments_lexer": "ipython3", |
1005 | | - "version": "3.9.5" |
| 1005 | + "version": "3.9.7" |
1006 | 1006 | } |
1007 | 1007 | }, |
1008 | 1008 | "nbformat": 4, |
|
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