{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session\n\nimport matplotlib.pyplot as plt","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2021-10-12T09:49:38.214534Z","iopub.execute_input":"2021-10-12T09:49:38.214832Z","iopub.status.idle":"2021-10-12T09:49:38.226369Z","shell.execute_reply.started":"2021-10-12T09:49:38.214798Z","shell.execute_reply":"2021-10-12T09:49:38.224563Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"players_df = pd.read_csv('/kaggle/input/nfl-big-data-bowl-2022/players.csv')\nplayers_df.head()","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.229169Z","iopub.execute_input":"2021-10-12T09:49:38.229510Z","iopub.status.idle":"2021-10-12T09:49:38.257928Z","shell.execute_reply.started":"2021-10-12T09:49:38.229467Z","shell.execute_reply":"2021-10-12T09:49:38.256964Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"players_df['Position'].value_counts()","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.259822Z","iopub.execute_input":"2021-10-12T09:49:38.260160Z","iopub.status.idle":"2021-10-12T09:49:38.268174Z","shell.execute_reply.started":"2021-10-12T09:49:38.260119Z","shell.execute_reply":"2021-10-12T09:49:38.267556Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(\"Average Weight in Possitions:\")\nprint(\"*****************************\")\nwr_df = players_df.loc[players_df['Position'] == 'WR']\nwr_weight = np.average(wr_df['weight'])\nprint(\"WR: \",wr_weight*0.45359237,\"kg\")\nwr_cb = players_df.loc[players_df['Position'] == 'CB']\ncb_weight = np.average(wr_cb['weight'])\nprint(\"CB: \",cb_weight*0.45359237,\"kg\")\nwr_de = players_df.loc[players_df['Position'] == 'DE']\nde_weight = np.average(wr_de['weight'])\nprint(\"CB: \",de_weight*0.45359237,\"kg\")\nwr_olb = players_df.loc[players_df['Position'] == 'OLB']\nolb_weight = np.average(wr_olb['weight'])\nprint(\"OLB:\",olb_weight*0.45359237,\"kg\")\nwr_te = players_df.loc[players_df['Position'] == 'TE']\nte_weight = np.average(wr_te['weight'])\nprint(\"TE: \",te_weight*0.45359237,\"kg\")\nwr_t = players_df.loc[players_df['Position'] == 'T']\nt_weight = np.average(wr_t['weight'])\nprint(\"T : \",t_weight*0.45359237,\"kg\")\nwr_rb = players_df.loc[players_df['Position'] == 'RB']\nrb_weight = np.average(wr_rb['weight'])\nprint(\"RB: \",rb_weight*0.45359237,\"kg\")\nwr_g = players_df.loc[players_df['Position'] == 'G']\ng_weight = np.average(wr_g['weight'])\nprint(\"G : \",g_weight*0.45359237,\"kg\")\nwr_dt = players_df.loc[players_df['Position'] == 'DT']\ndt_weight = np.average(wr_dt['weight'])\nprint(\"DT :\",dt_weight*0.45359237,\"kg\")\nwr_ilb = players_df.loc[players_df['Position'] == 'ILB']\nilb_weight = np.average(wr_ilb['weight'])\nprint(\"ILB:\",ilb_weight*0.45359237,\"kg\")\nwr_fs = players_df.loc[players_df['Position'] == 'FS']\nfs_weight = np.average(wr_fs['weight'])\nprint(\"FS :\",fs_weight*0.45359237,\"kg\")\nwr_ss = players_df.loc[players_df['Position'] == 'SS']\nss_weight = np.average(wr_ss['weight'])\nprint(\"SS :\",ss_weight*0.45359237,\"kg\")\nwr_c = players_df.loc[players_df['Position'] == 'C']\nc_weight = np.average(wr_c['weight'])\nprint(\"C  :\",c_weight*0.45359237,\"kg\")\nwr_k = players_df.loc[players_df['Position'] == 'K']\nk_weight = np.average(wr_k['weight'])\nprint(\"K  :\",k_weight*0.45359237,\"kg\")\nwr_p = players_df.loc[players_df['Position'] == 'P']\np_weight = np.average(wr_p['weight'])\nprint(\"P  :\",p_weight*0.45359237,\"kg\")\nwr_nt = players_df.loc[players_df['Position'] == 'NT']\nnt_weight = np.average(wr_nt['weight'])\nprint(\"NT :\",nt_weight*0.45359237,\"kg\")\nwr_ls = players_df.loc[players_df['Position'] == 'LS']\nls_weight = np.average(wr_ls['weight'])\nprint(\"LS :\",ls_weight*0.45359237,\"kg\")\nwr_db = players_df.loc[players_df['Position'] == 'DB']\ndb_weight = np.average(wr_db['weight'])\nprint(\"DB :\",db_weight*0.45359237,\"kg\")\nwr_lb = players_df.loc[players_df['Position'] == 'LB']\nlb_weight = np.average(wr_lb['weight'])\nprint(\"LB :\",lb_weight*0.45359237,\"kg\")\nwr_mlb = players_df.loc[players_df['Position'] == 'MLB']\nmlb_weight = np.average(wr_mlb['weight'])\nprint(\"MLB:\",mlb_weight*0.45359237,\"kg\")\nwr_fb = players_df.loc[players_df['Position'] == 'FB']\nfb_weight = np.average(wr_fb['weight'])\nprint(\"FB :\",fb_weight*0.45359237,\"kg\")\nwr_ot = players_df.loc[players_df['Position'] == 'OT']\not_weight = np.average(wr_ot['weight'])\nprint(\"OT :\",ot_weight*0.45359237,\"kg\")\nwr_qb = players_df.loc[players_df['Position'] == 'QB']\nqb_weight = np.average(wr_qb['weight'])\nprint(\"QB :\",qb_weight*0.45359237,\"kg\")\nwr_s = players_df.loc[players_df['Position'] == 'S']\ns_weight = np.average(wr_s['weight'])\nprint(\"S  :\",s_weight*0.45359237,\"kg\")\nwr_og = players_df.loc[players_df['Position'] == 'OG']\nog_weight = np.average(wr_og['weight'])\nprint(\"OG :\",og_weight*0.45359237,\"kg\")\nwr_hb = players_df.loc[players_df['Position'] == 'HB']\nhb_weight = np.average(wr_hb['weight'])\nprint(\"HB :\",hb_weight*0.45359237,\"kg\")\nprint(\"*******************************\")\nprint(\"NFL player average weight:\")\ntotal_weight = np.average(players_df['weight'])\nprint(\"Total\",total_weight*0.45359237,\"kg\")\n","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.269361Z","iopub.execute_input":"2021-10-12T09:49:38.269593Z","iopub.status.idle":"2021-10-12T09:49:38.346085Z","shell.execute_reply.started":"2021-10-12T09:49:38.269568Z","shell.execute_reply":"2021-10-12T09:49:38.345230Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"height_dict = {\n    \"5-10\": 178,\n    \"5-11\": 180,\n    \"5-6\": 168,\n    \"5-7\": 170,\n    \"5-8\": 173,\n    \"5-9\": 175,\n    \"6-0\": 183,\n    \"6-1\": 185,\n    \"6-2\": 188,\n    \"6-3\": 190,\n    \"6-4\": 193,\n    \"6-5\": 196,\n    \"6-6\": 198,\n    \"6-7\": 201,\n    \"6-8\": 203,\n    \"6-9\": 206,\n    \"66\": 168,\n    \"67\": 170,\n    \"68\": 173,\n    \"69\": 175,\n    \"70\": 178,\n    \"71\": 180,\n    \"72\": 183,\n    \"73\": 185,\n    \"74\": 188,\n    \"75\": 191,\n    \"76\": 193,\n    \"77\": 196,\n    \"78\": 198,\n    \"79\": 201\n}","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.348666Z","iopub.execute_input":"2021-10-12T09:49:38.348888Z","iopub.status.idle":"2021-10-12T09:49:38.356503Z","shell.execute_reply.started":"2021-10-12T09:49:38.348862Z","shell.execute_reply":"2021-10-12T09:49:38.355666Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"players_df[\"height_cm\"] = players_df[\"height\"].replace(height_dict)\nplayers_df","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.357846Z","iopub.execute_input":"2021-10-12T09:49:38.358191Z","iopub.status.idle":"2021-10-12T09:49:38.400622Z","shell.execute_reply.started":"2021-10-12T09:49:38.358160Z","shell.execute_reply":"2021-10-12T09:49:38.399683Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(\"Average Height in Possitions:\")\nprint(\"*****************************\")\nwr_df = players_df.loc[players_df['Position'] == 'WR']\nwr_height = np.average(wr_df['height_cm'])\nprint(\"WR: \",wr_height,\"cm\")\nwr_cb = players_df.loc[players_df['Position'] == 'CB']\ncb_height = np.average(wr_cb['height_cm'])\nprint(\"CB: \",cb_height,\"cm\")\nwr_de = players_df.loc[players_df['Position'] == 'DE']\nde_height = np.average(wr_de['height_cm'])\nprint(\"CB: \",de_height,\"cm\")\nwr_olb = players_df.loc[players_df['Position'] == 'OLB']\nolb_height = np.average(wr_olb['height_cm'])\nprint(\"OLB:\",olb_height,\"cm\")\nwr_te = players_df.loc[players_df['Position'] == 'TE']\nte_height = np.average(wr_te['height_cm'])\nprint(\"TE: \",te_height,\"cm\")\nwr_t = players_df.loc[players_df['Position'] == 'T']\nt_height = np.average(wr_t['height_cm'])\nprint(\"T : \",t_height,\"cm\")\nwr_rb = players_df.loc[players_df['Position'] == 'RB']\nrb_height = np.average(wr_rb['height_cm'])\nprint(\"RB: \",rb_height,\"cm\")\nwr_g = players_df.loc[players_df['Position'] == 'G']\ng_height = np.average(wr_g['height_cm'])\nprint(\"G : \",g_height,\"cm\")\nwr_dt = players_df.loc[players_df['Position'] == 'DT']\ndt_height = np.average(wr_dt['height_cm'])\nprint(\"DT :\",dt_height,\"cm\")\nwr_ilb = players_df.loc[players_df['Position'] == 'ILB']\nilb_height = np.average(wr_ilb['height_cm'])\nprint(\"ILB:\",ilb_height,\"cm\")\nwr_fs = players_df.loc[players_df['Position'] == 'FS']\nfs_height = np.average(wr_fs['height_cm'])\nprint(\"FS :\",fs_height,\"cm\")\nwr_ss = players_df.loc[players_df['Position'] == 'SS']\nss_height = np.average(wr_ss['height_cm'])\nprint(\"SS :\",ss_height,\"cm\")\nwr_c = players_df.loc[players_df['Position'] == 'C']\nc_height = np.average(wr_c['height_cm'])\nprint(\"C  :\",c_height,\"cm\")\nwr_k = players_df.loc[players_df['Position'] == 'K']\nk_height = np.average(wr_k['height_cm'])\nprint(\"K  :\",k_height,\"cm\")\nwr_p = players_df.loc[players_df['Position'] == 'P']\np_height = np.average(wr_p['height_cm'])\nprint(\"P  :\",p_height,\"cm\")\nwr_nt = players_df.loc[players_df['Position'] == 'NT']\nnt_height = np.average(wr_nt['height_cm'])\nprint(\"NT :\",nt_height,\"cm\")\nwr_ls = players_df.loc[players_df['Position'] == 'LS']\nls_height = np.average(wr_ls['height_cm'])\nprint(\"LS :\",ls_height,\"cm\")\nwr_db = players_df.loc[players_df['Position'] == 'DB']\ndb_height = np.average(wr_db['height_cm'])\nprint(\"DB :\",db_height,\"cm\")\nwr_lb = players_df.loc[players_df['Position'] == 'LB']\nlb_height = np.average(wr_lb['height_cm'])\nprint(\"LB :\",lb_height,\"cm\")\nwr_mlb = players_df.loc[players_df['Position'] == 'MLB']\nmlb_height = np.average(wr_mlb['height_cm'])\nprint(\"MLB:\",mlb_height,\"cm\")\nwr_fb = players_df.loc[players_df['Position'] == 'FB']\nfb_height = np.average(wr_fb['height_cm'])\nprint(\"FB :\",fb_height,\"cm\")\nwr_ot = players_df.loc[players_df['Position'] == 'OT']\not_height = np.average(wr_ot['height_cm'])\nprint(\"OT :\",ot_height,\"cm\")\nwr_qb = players_df.loc[players_df['Position'] == 'QB']\nqb_height = np.average(wr_qb['height_cm'])\nprint(\"QB :\",qb_height,\"cm\")\nwr_s = players_df.loc[players_df['Position'] == 'S']\ns_height = np.average(wr_s['height_cm'])\nprint(\"S  :\",s_height,\"cm\")\nwr_og = players_df.loc[players_df['Position'] == 'OG']\nog_height = np.average(wr_og['height_cm'])\nprint(\"OG :\",og_height,\"cm\")\nwr_hb = players_df.loc[players_df['Position'] == 'HB']\nhb_height = np.average(wr_hb['height_cm'])\nprint(\"HB :\",hb_height,\"cm\")\nprint(\"*******************************\")\nprint(\"NFL player average height:\")\n    \ntotal_height = np.average(players_df['height_cm'])\nprint(\"Total\",total_height,\"cm\")","metadata":{"execution":{"iopub.status.busy":"2021-10-12T09:49:38.402353Z","iopub.execute_input":"2021-10-12T09:49:38.402699Z","iopub.status.idle":"2021-10-12T09:49:38.479266Z","shell.execute_reply.started":"2021-10-12T09:49:38.402655Z","shell.execute_reply":"2021-10-12T09:49:38.478350Z"},"trusted":true},"execution_count":null,"outputs":[]}]}