{"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":"markdown","source":"# BirdCLEF_2022_EDA🦜🐦🎶","metadata":{}},{"cell_type":"markdown","source":"# Let's make the best way and protect the endangered Hawaiian birds.\n\n![download.jpg](attachment:4debb761-b480-4659-8b9a-fea3f33335a5.jpg)\n* 'I'IWI[ Image photo by :Sherman Wing \"Hawai'i Birding Trails\"](https://hawaiibirdingtrails.hawaii.gov/bird/)\n","metadata":{},"attachments":{"4debb761-b480-4659-8b9a-fea3f33335a5.jpg":{"image/jpeg":"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"}}},{"cell_type":"markdown","source":"# What kind of birds are in Hawaii? \n\n* These birds are only found in Hawaii.\n* [APAPANE](http:/https://hawaiibirdingtrails.hawaii.gov/bird/apapane/)\n* [HAWAII ELEPAIO](https://hawaiibirdingtrails.hawaii.gov/bird/hawaii-elepaio/)\n* [HAWAII AMAKIHI](https://hawaiibirdingtrails.hawaii.gov/bird/hawaii-amakihi/)\n* ['I'IWI](https://hawaiibirdingtrails.hawaii.gov/bird/iiwi/)\n\n\n* These Hawaiian birds are endangered.\n* [HAWAII AKEPA ](https://hawaiibirdingtrails.hawaii.gov/bird/hawaii-akepa/)\n* [AKIAPOLAAU](https://hawaiibirdingtrails.hawaii.gov/bird/akiapolaau/)\n* [ʻĀKOHEKOHE](https://hawaiibirdingtrails.hawaii.gov/bird/akohekohe/)\n* [HAWAII CREEPER](https://hawaiibirdingtrails.hawaii.gov/bird/hawaii-creeper/)\n* [HAWAIIAN GOOSE/ NĒNĒ](https://hawaiibirdingtrails.hawaii.gov/bird/hawaiian-goose/)\n* [MAUI PARROTBILL](https://hawaiibirdingtrails.hawaii.gov/bird/maui-parrotbill/)\n* [ʻŌMAʻO](https://hawaiibirdingtrails.hawaii.gov/bird/omao/)\n* [PALILA](https://hawaiibirdingtrails.hawaii.gov/bird/palila/)\n\n\n* Please see below for onther birds information\n* [eBird:TheCoenellLabofOmithology](https://ebird.org/home/)\n* [xeno-canto](https://xeno-canto.org/)\n* [Hawai'i Birding Trails](https://hawaiibirdingtrails.hawaii.gov/bird/)\n* [List of birds of Hawaii: wiki](https://en.wikipedia.org/wiki/List_of_birds_of_Hawaii/)\n","metadata":{}},{"cell_type":"code","source":"!pip install '../input/noisereduce-2-0-0/noisereduce-2.0.0-py3-none-any.whl'","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2022-05-24T22:47:29.429621Z","iopub.execute_input":"2022-05-24T22:47:29.429917Z","iopub.status.idle":"2022-05-24T22:47:58.297999Z","shell.execute_reply.started":"2022-05-24T22:47:29.429885Z","shell.execute_reply":"2022-05-24T22:47:58.296912Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pip install wordcloud","metadata":{"_kg_hide-input":true,"_kg_hide-output":true,"execution":{"iopub.status.busy":"2022-05-24T22:47:58.300280Z","iopub.execute_input":"2022-05-24T22:47:58.300555Z","iopub.status.idle":"2022-05-24T22:48:26.972393Z","shell.execute_reply.started":"2022-05-24T22:47:58.300519Z","shell.execute_reply":"2022-05-24T22:48:26.971681Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import os\nimport re\nimport ast\nimport json\nimport random\nimport numpy as np\nimport pandas as pd\nimport soundfile as sf\nimport geopandas as gpd\nimport noisereduce as nr\nfrom datetime import datetime, timedelta\n\nfrom wordcloud import WordCloud\n#from PIL import Image\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nsns.set('notebook','darkgrid', 'rainbow')\n\n%matplotlib inline\n\nimport librosa\nimport librosa.display\n\nimport IPython.display as display\nfrom IPython.display import Image\nfrom IPython.display import Audio\nimport IPython.display as ipd\n\nimport folium\nfrom folium import Choropleth, Circle, Marker\nfrom folium.plugins import HeatMap, MarkerCluster\n\nfrom itertools import cycle\ncolor_cycle = cycle(plt.rcParams[\"axes.prop_cycle\"].by_key()[\"color\"])\n\nimport plotly.express as px\nfrom scipy.fft import fft, fftfreq\n\npath = '/kaggle/input/birdclef-2022/'\nos.listdir(path)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:26.973817Z","iopub.execute_input":"2022-05-24T22:48:26.974074Z","iopub.status.idle":"2022-05-24T22:48:26.999411Z","shell.execute_reply.started":"2022-05-24T22:48:26.974043Z","shell.execute_reply":"2022-05-24T22:48:26.998524Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"path_ex = '/kaggle/input/'\nos.listdir(path_ex)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:27.002008Z","iopub.execute_input":"2022-05-24T22:48:27.002530Z","iopub.status.idle":"2022-05-24T22:48:27.009157Z","shell.execute_reply.started":"2022-05-24T22:48:27.002485Z","shell.execute_reply":"2022-05-24T22:48:27.008389Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train = pd.read_csv(path+'train_metadata.csv')\ntest = pd.read_csv(path+'test.csv')\nebird = pd.read_csv(path+'eBird_Taxonomy_v2021.csv')\nsub = pd.read_csv(path+'sample_submission.csv')\n\ntrain_ex_am = pd.read_csv(path_ex +'xeno-canto-bird-recordings-extended-a-m/train_extended.csv')\ntrain_ex_nz = pd.read_csv(path_ex +'xeno-canto-bird-recordings-extended-n-z/train_extended.csv')\n\nBASE_DIR = '../input/birdclef-2022/'\nDATA_DIR ='../input/birdclef-2022/train_audio'\n\nwith open(path+'scored_birds.json') as f:\n    scored_birds = json.load(f)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.010734Z","iopub.execute_input":"2022-05-24T22:48:27.011244Z","iopub.status.idle":"2022-05-24T22:48:27.686902Z","shell.execute_reply.started":"2022-05-24T22:48:27.011201Z","shell.execute_reply":"2022-05-24T22:48:27.685691Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"===================================\n# Test Soundscapes\n","metadata":{}},{"cell_type":"code","source":"os.listdir(path+'test_soundscapes')","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.688246Z","iopub.execute_input":"2022-05-24T22:48:27.688497Z","iopub.status.idle":"2022-05-24T22:48:27.694592Z","shell.execute_reply.started":"2022-05-24T22:48:27.688466Z","shell.execute_reply":"2022-05-24T22:48:27.694001Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"==================================\n# Train Data(metadata)","metadata":{}},{"cell_type":"code","source":"train.head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.695720Z","iopub.execute_input":"2022-05-24T22:48:27.695932Z","iopub.status.idle":"2022-05-24T22:48:27.719250Z","shell.execute_reply.started":"2022-05-24T22:48:27.695906Z","shell.execute_reply":"2022-05-24T22:48:27.718360Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.info()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.720344Z","iopub.execute_input":"2022-05-24T22:48:27.720912Z","iopub.status.idle":"2022-05-24T22:48:27.756503Z","shell.execute_reply.started":"2022-05-24T22:48:27.720877Z","shell.execute_reply":"2022-05-24T22:48:27.755633Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train.iloc[0]","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.758086Z","iopub.execute_input":"2022-05-24T22:48:27.758596Z","iopub.status.idle":"2022-05-24T22:48:27.766988Z","shell.execute_reply.started":"2022-05-24T22:48:27.758551Z","shell.execute_reply":"2022-05-24T22:48:27.766161Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"> train data is non_null and Dtype is object and float64.","metadata":{}},{"cell_type":"markdown","source":"==================================\n# Test Data","metadata":{}},{"cell_type":"code","source":"test.head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.770073Z","iopub.execute_input":"2022-05-24T22:48:27.770330Z","iopub.status.idle":"2022-05-24T22:48:27.784923Z","shell.execute_reply.started":"2022-05-24T22:48:27.770301Z","shell.execute_reply":"2022-05-24T22:48:27.784173Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test.info()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.786067Z","iopub.execute_input":"2022-05-24T22:48:27.786659Z","iopub.status.idle":"2022-05-24T22:48:27.803228Z","shell.execute_reply.started":"2022-05-24T22:48:27.786624Z","shell.execute_reply":"2022-05-24T22:48:27.802053Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"> test data is non_null and Dtype is object and int64.","metadata":{}},{"cell_type":"markdown","source":"==================================\n# xeno-canto-bird_recoding_extend","metadata":{}},{"cell_type":"code","source":"train_ex = pd.concat([train_ex_am ,train_ex_nz])","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.804871Z","iopub.execute_input":"2022-05-24T22:48:27.805221Z","iopub.status.idle":"2022-05-24T22:48:27.850517Z","shell.execute_reply.started":"2022-05-24T22:48:27.805176Z","shell.execute_reply":"2022-05-24T22:48:27.849626Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.851887Z","iopub.execute_input":"2022-05-24T22:48:27.852258Z","iopub.status.idle":"2022-05-24T22:48:27.880068Z","shell.execute_reply.started":"2022-05-24T22:48:27.852212Z","shell.execute_reply":"2022-05-24T22:48:27.878972Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.info()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:27.881734Z","iopub.execute_input":"2022-05-24T22:48:27.882039Z","iopub.status.idle":"2022-05-24T22:48:28.020455Z","shell.execute_reply.started":"2022-05-24T22:48:27.881998Z","shell.execute_reply":"2022-05-24T22:48:28.019483Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.species.describe()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:28.021913Z","iopub.execute_input":"2022-05-24T22:48:28.022310Z","iopub.status.idle":"2022-05-24T22:48:28.044880Z","shell.execute_reply.started":"2022-05-24T22:48:28.022265Z","shell.execute_reply":"2022-05-24T22:48:28.043923Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.drop('xc_id', axis=1, inplace = True)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:28.046374Z","iopub.execute_input":"2022-05-24T22:48:28.046608Z","iopub.status.idle":"2022-05-24T22:48:28.081018Z","shell.execute_reply.started":"2022-05-24T22:48:28.046572Z","shell.execute_reply":"2022-05-24T22:48:28.080141Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(24, 10))\ng = sns.countplot(data = train_ex[:5000], x = \"ebird_code\")\n\nplt.title(\"Species\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.xticks(rotation=90)\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:28.082572Z","iopub.execute_input":"2022-05-24T22:48:28.082909Z","iopub.status.idle":"2022-05-24T22:48:30.250762Z","shell.execute_reply.started":"2022-05-24T22:48:28.082867Z","shell.execute_reply":"2022-05-24T22:48:30.249788Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(24, 10))\ng = sns.countplot(data = train_ex[5000:10000], x = \"ebird_code\")\n\nplt.title(\"Species\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.xticks(rotation=90)\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:30.252092Z","iopub.execute_input":"2022-05-24T22:48:30.252339Z","iopub.status.idle":"2022-05-24T22:48:31.207580Z","shell.execute_reply.started":"2022-05-24T22:48:30.252310Z","shell.execute_reply":"2022-05-24T22:48:31.206931Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.elevation.describe()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:31.208691Z","iopub.execute_input":"2022-05-24T22:48:31.209014Z","iopub.status.idle":"2022-05-24T22:48:31.229845Z","shell.execute_reply.started":"2022-05-24T22:48:31.208985Z","shell.execute_reply":"2022-05-24T22:48:31.228871Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(24, 10))\ng = sns.countplot(data = train_ex[:1000], x = \"elevation\")\n\nplt.title(\"Elevation\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\n    \nplt.xticks(rotation=90)   \nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:31.231087Z","iopub.execute_input":"2022-05-24T22:48:31.231399Z","iopub.status.idle":"2022-05-24T22:48:33.905586Z","shell.execute_reply.started":"2022-05-24T22:48:31.231367Z","shell.execute_reply":"2022-05-24T22:48:33.904651Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex['rating']","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:33.906799Z","iopub.execute_input":"2022-05-24T22:48:33.907020Z","iopub.status.idle":"2022-05-24T22:48:33.916566Z","shell.execute_reply.started":"2022-05-24T22:48:33.906993Z","shell.execute_reply":"2022-05-24T22:48:33.915562Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(10, 6))\ng = sns.countplot(data = train_ex, x = \"rating\")\n\nplt.title(\"Ratimg\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:33.918134Z","iopub.execute_input":"2022-05-24T22:48:33.919195Z","iopub.status.idle":"2022-05-24T22:48:34.241514Z","shell.execute_reply.started":"2022-05-24T22:48:33.919147Z","shell.execute_reply":"2022-05-24T22:48:34.240512Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.groupby('rating').mean().astype(int).T.style.bar( align = 'mid', width = 90, axis = None, color = ['#d65f5f','#5fba7d'])","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:34.243158Z","iopub.execute_input":"2022-05-24T22:48:34.243386Z","iopub.status.idle":"2022-05-24T22:48:34.283907Z","shell.execute_reply.started":"2022-05-24T22:48:34.243358Z","shell.execute_reply":"2022-05-24T22:48:34.283029Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(10, 6))\ng = sns.countplot(data = train_ex, x = \"sampling_rate\")\n\nplt.title(\"Sampling_rate\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.xticks(rotation=90)     \nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:34.285162Z","iopub.execute_input":"2022-05-24T22:48:34.285472Z","iopub.status.idle":"2022-05-24T22:48:34.636573Z","shell.execute_reply.started":"2022-05-24T22:48:34.285431Z","shell.execute_reply":"2022-05-24T22:48:34.635904Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.groupby('sampling_rate').mean().astype(int).style.bar( align = 'mid', width = 90, axis = None, color = ['#d65f5f','#5fba7d'])","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:34.637732Z","iopub.execute_input":"2022-05-24T22:48:34.638175Z","iopub.status.idle":"2022-05-24T22:48:34.679004Z","shell.execute_reply.started":"2022-05-24T22:48:34.638130Z","shell.execute_reply":"2022-05-24T22:48:34.677842Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(10, 6))\ng = sns.countplot(data = train_ex, x = \"bird_seen\")\n\nplt.title(\"Bird_seen\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:34.680527Z","iopub.execute_input":"2022-05-24T22:48:34.680785Z","iopub.status.idle":"2022-05-24T22:48:34.935320Z","shell.execute_reply.started":"2022-05-24T22:48:34.680754Z","shell.execute_reply":"2022-05-24T22:48:34.934674Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_ex.to_csv(\"train_ex.csv\")  ","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:34.936655Z","iopub.execute_input":"2022-05-24T22:48:34.937095Z","iopub.status.idle":"2022-05-24T22:48:36.350412Z","shell.execute_reply.started":"2022-05-24T22:48:34.937060Z","shell.execute_reply":"2022-05-24T22:48:36.349683Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* I added these data. I will try to using this data.","metadata":{}},{"cell_type":"markdown","source":"==================================\n# scored_birds (scored_birds.json)","metadata":{}},{"cell_type":"code","source":"train_p = train[train['primary_label'].isin(scored_birds)]\ntrain_p.head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:36.357273Z","iopub.execute_input":"2022-05-24T22:48:36.357821Z","iopub.status.idle":"2022-05-24T22:48:36.380730Z","shell.execute_reply.started":"2022-05-24T22:48:36.357769Z","shell.execute_reply":"2022-05-24T22:48:36.379888Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"scored_birds = train_p[\"primary_label\"].unique()\nprint(len(scored_birds))\nscored_birds","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:36.382444Z","iopub.execute_input":"2022-05-24T22:48:36.383012Z","iopub.status.idle":"2022-05-24T22:48:36.391503Z","shell.execute_reply.started":"2022-05-24T22:48:36.382968Z","shell.execute_reply":"2022-05-24T22:48:36.390652Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize =(10, 6))\ng = sns.countplot(data = train_p, x = \"rating\")\n\nplt.title(\"Rating\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:36.392946Z","iopub.execute_input":"2022-05-24T22:48:36.393923Z","iopub.status.idle":"2022-05-24T22:48:36.710310Z","shell.execute_reply.started":"2022-05-24T22:48:36.393875Z","shell.execute_reply":"2022-05-24T22:48:36.709404Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"[](http://)","metadata":{}},{"cell_type":"markdown","source":"===================================\n# eBird(eBird_Taxonomy_v2021)\n* [2021 eBird Taxonomy Update — COMPLETE](https://ebird.org/news/2021-ebird-taxonomy-update/)\n* [eBird_Taxonomy:Help Center](https://support.ebird.org/en/support/solutions/articles/48000837816-the-ebird-taxonomy/)","metadata":{}},{"cell_type":"code","source":"ebird.head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:36.711818Z","iopub.execute_input":"2022-05-24T22:48:36.712171Z","iopub.status.idle":"2022-05-24T22:48:36.728012Z","shell.execute_reply.started":"2022-05-24T22:48:36.712119Z","shell.execute_reply":"2022-05-24T22:48:36.726834Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"ebird.info()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:36.729970Z","iopub.execute_input":"2022-05-24T22:48:36.730549Z","iopub.status.idle":"2022-05-24T22:48:36.758071Z","shell.execute_reply.started":"2022-05-24T22:48:36.730511Z","shell.execute_reply":"2022-05-24T22:48:36.757471Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.set('notebook','darkgrid', 'rainbow')\nfig, ax = plt.subplots(figsize =(10, 6))\ng = sns.countplot(data = ebird, x = \"CATEGORY\")\n\nplt.title(\"Record count per Category\")\nfor p in g.patches:\n    g.annotate(format(p.get_height(), '.0f'), (p.get_x() + p.get_width() / 2., p.get_height()), ha = 'center', va = 'center', xytext = (0, 10), textcoords = 'offset points')\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:36.759054Z","iopub.execute_input":"2022-05-24T22:48:36.759638Z","iopub.status.idle":"2022-05-24T22:48:37.053444Z","shell.execute_reply.started":"2022-05-24T22:48:36.759605Z","shell.execute_reply":"2022-05-24T22:48:37.052855Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* [@PRAVEEN KUMAR/🐦 BirdCLEF 2022: EDA 🐦](https://www.kaggle.com/prokaggler/birdclef-2022-eda/)\n","metadata":{}},{"cell_type":"markdown","source":"==================================\n# Train audio🎧","metadata":{}},{"cell_type":"code","source":"print('Number of train_audio/species:', len(os.listdir(path+'train_audio')))\nprint(\"Example\")\nfn = train[\"filename\"].values[1]\nipd.Audio(f\"{BASE_DIR}train_audio/{fn}\")","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:37.054610Z","iopub.execute_input":"2022-05-24T22:48:37.054925Z","iopub.status.idle":"2022-05-24T22:48:37.083941Z","shell.execute_reply.started":"2022-05-24T22:48:37.054897Z","shell.execute_reply":"2022-05-24T22:48:37.083158Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"😌🎵","metadata":{}},{"cell_type":"markdown","source":"==================================\n# Primary_label & Common_name🦆","metadata":{}},{"cell_type":"code","source":"birds_name = pd.DataFrame( train[['common_name','primary_label']])\nprint(len(birds_name))\nbirds_name","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:37.085276Z","iopub.execute_input":"2022-05-24T22:48:37.086127Z","iopub.status.idle":"2022-05-24T22:48:37.105010Z","shell.execute_reply.started":"2022-05-24T22:48:37.086047Z","shell.execute_reply":"2022-05-24T22:48:37.104322Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#n = 0\n#for i in range(6):\n    #print(birds_name.value_counts()[n: n+30])\n    #n += 30  ","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:37.106415Z","iopub.execute_input":"2022-05-24T22:48:37.106962Z","iopub.status.idle":"2022-05-24T22:48:37.110937Z","shell.execute_reply.started":"2022-05-24T22:48:37.106914Z","shell.execute_reply":"2022-05-24T22:48:37.110048Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(16, 28))\n\nsns.countplot(data=train, y = 'primary_label', ax=ax, order=train['primary_label'].value_counts().index,)\nsns.countplot(data=train_p, y = 'primary_label', ax=ax, order=train['primary_label'].value_counts().index, color = 'red')\nplt.title('Birds count: Red line is scored_birds',fontdict = {'fontsize':18})\nplt.legend()\nplt.show()\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:37.112415Z","iopub.execute_input":"2022-05-24T22:48:37.112651Z","iopub.status.idle":"2022-05-24T22:48:39.836074Z","shell.execute_reply.started":"2022-05-24T22:48:37.112622Z","shell.execute_reply":"2022-05-24T22:48:39.835066Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"==================================\n# When are birds singing?⌚","metadata":{}},{"cell_type":"code","source":"def round_date(date, delta = 30, th = 10):\n    date = date.to_pydatetime()\n    x = date.minute\n    if ((x >= (delta - th)) & (x < delta)) or (x > (delta + th)):\n#         print('Up')\n        date = date + (datetime.min - date) % timedelta(minutes = delta)\n    elif ((x <= (delta+ th )) & (x > delta)) or (x < (delta - th)):\n#         print('down')\n        date = date - (date - datetime.min) % timedelta(minutes = delta)\n\n    \n    return date.time().strftime(\"%H:%M\")\n\ntrain['time_tf']  = pd.to_datetime(train['time'], errors = 'coerce').dropna().apply(lambda x:round_date(x))\ntrain.dropna(subset=['time_tf'], inplace = True)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:39.837482Z","iopub.execute_input":"2022-05-24T22:48:39.837875Z","iopub.status.idle":"2022-05-24T22:48:40.103524Z","shell.execute_reply.started":"2022-05-24T22:48:39.837829Z","shell.execute_reply":"2022-05-24T22:48:40.102581Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize = (15,8))\nsns.countplot(x = 'time_tf', data = train.sort_values(by = 'time_tf'))\nplt.xticks(rotation=45)\nplt.xlabel('Time', fontdict = {'fontsize':18})\nplt.ylabel('Frequency', fontdict = {'fontsize':18})\nplt.title('Birds Registers\\' Time',fontdict = {'fontsize':18})\nplt.tight_layout()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:40.104911Z","iopub.execute_input":"2022-05-24T22:48:40.105161Z","iopub.status.idle":"2022-05-24T22:48:41.283228Z","shell.execute_reply.started":"2022-05-24T22:48:40.105133Z","shell.execute_reply":"2022-05-24T22:48:41.282289Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* It must be an owl at night🦉 hoot!\n* Which is tne early bird?🐓\n\n* [@PAULO JUNQUEIRA/🐥 Little Bird, what sound is that? - EDA](https://www.kaggle.com/paulojunqueira/little-bird-what-sound-is-that-eda)\n","metadata":{}},{"cell_type":"markdown","source":"==================================\n# Secondary_label","metadata":{}},{"cell_type":"code","source":"train['secondary_labels'].head(3)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:41.284714Z","iopub.execute_input":"2022-05-24T22:48:41.284942Z","iopub.status.idle":"2022-05-24T22:48:41.291970Z","shell.execute_reply.started":"2022-05-24T22:48:41.284915Z","shell.execute_reply":"2022-05-24T22:48:41.291194Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"labels = []\nfor row in train.index:\n    labels.extend(ast.literal_eval(train.loc[row, 'secondary_labels']))\nlabels = list(set(labels))\n\nprint('Number of unique bird labels:', len(labels))\n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:41.293281Z","iopub.execute_input":"2022-05-24T22:48:41.294012Z","iopub.status.idle":"2022-05-24T22:48:41.603494Z","shell.execute_reply.started":"2022-05-24T22:48:41.293977Z","shell.execute_reply":"2022-05-24T22:48:41.602546Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train['secondary_labels'] = train['secondary_labels'].apply(lambda x: re.findall(r\"'(\\w+)'\", x))","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:41.604733Z","iopub.execute_input":"2022-05-24T22:48:41.604962Z","iopub.status.idle":"2022-05-24T22:48:41.632282Z","shell.execute_reply.started":"2022-05-24T22:48:41.604934Z","shell.execute_reply":"2022-05-24T22:48:41.631011Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"data_1 = train['secondary_labels'].explode().value_counts().head(50).reset_index()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:41.633858Z","iopub.execute_input":"2022-05-24T22:48:41.634680Z","iopub.status.idle":"2022-05-24T22:48:41.651764Z","shell.execute_reply.started":"2022-05-24T22:48:41.634633Z","shell.execute_reply":"2022-05-24T22:48:41.650876Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\nfig, ax = plt.subplots( figsize = (10,8))\nsns.barplot(y = 'index', x = 'secondary_labels',data = data_1[1:],ax = ax)\nax.set_title(\" Birds Found on Background as Noise\", fontdict = {'fontsize':20})\nax.set_xlabel('Frequency', fontdict = {'fontsize':16})\nax.set_ylabel('Birds Common Name', fontdict = {'fontsize':16})\n\nplt.tight_layout()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:48:41.653031Z","iopub.execute_input":"2022-05-24T22:48:41.653501Z","iopub.status.idle":"2022-05-24T22:48:42.454820Z","shell.execute_reply.started":"2022-05-24T22:48:41.653456Z","shell.execute_reply":"2022-05-24T22:48:42.453923Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* Do we need to remove the noise?How?--> using noise reduction\n* [@PAULO JUNQUEIRA/🐥 Little Bird, what sound is that? - EDA](https://www.kaggle.com/paulojunqueira/little-bird-what-sound-is-that-eda)","metadata":{}},{"cell_type":"code","source":"text = \" \".join(i for i in train_ex['ebird_code'])\nword_cloud = WordCloud(width=1600, height=800, collocations = False, background_color = 'white').generate(text)\nplt.figure(figsize=[14, 8])\nplt.imshow(word_cloud)\nplt.axis(\"off\")\nplt.title(\"ebird_code\")\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:42.456111Z","iopub.execute_input":"2022-05-24T22:48:42.456377Z","iopub.status.idle":"2022-05-24T22:48:45.912454Z","shell.execute_reply.started":"2022-05-24T22:48:42.456347Z","shell.execute_reply":"2022-05-24T22:48:45.911307Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"text = \" \".join(i for i in train['primary_label'])\nword_cloud = WordCloud(width=1600, height=800, collocations = False, background_color = 'white').generate(text)\nplt.figure(figsize=[14, 8])\nplt.imshow(word_cloud)\nplt.axis(\"off\")\nplt.title(\"Primary_label\")\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:45.913956Z","iopub.execute_input":"2022-05-24T22:48:45.914374Z","iopub.status.idle":"2022-05-24T22:48:48.861385Z","shell.execute_reply.started":"2022-05-24T22:48:45.914332Z","shell.execute_reply":"2022-05-24T22:48:48.860658Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"text = \" \".join(i for i in scored_birds)\nword_cloud = WordCloud(width=1600, height=800, collocations = False, background_color = 'white').generate(text)\nplt.figure(figsize=[14, 8])\nplt.imshow(word_cloud)\nplt.axis(\"off\")\nplt.title(\"scored_birds\")\nplt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:48.863300Z","iopub.execute_input":"2022-05-24T22:48:48.863798Z","iopub.status.idle":"2022-05-24T22:48:50.420019Z","shell.execute_reply.started":"2022-05-24T22:48:48.863762Z","shell.execute_reply":"2022-05-24T22:48:50.418923Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* There are many different birds in the eBird and Xeno,so I will focus on Hawaiian birds.","metadata":{}},{"cell_type":"markdown","source":"==================================\n# Bird distribution map🔍","metadata":{}},{"cell_type":"code","source":"# initialize an axis\nfig, ax = plt.subplots(figsize=(26,20))\n# plot map on axis\ncountries = gpd.read_file(gpd.datasets.get_path(\"naturalearth_lowres\"))\ncountries.plot(color=\"lightgrey\", ax=ax)\n\n# plot points\ncmap = plt.cm.get_cmap('jet')\nbirds = len(train[\"primary_label\"].unique())\nfor i, (bird, dfg) in enumerate(train.groupby(\"primary_label\")):\n    dfg.longitude = np.around(dfg.longitude, 1)\n    dfg.latitude = np.around(dfg.latitude, 1)\n    dfgg = dfg.groupby([\"longitude\", \"latitude\"]).size().reset_index(name=\"counts\")\n    dfgg.plot(x=\"longitude\", y=\"latitude\", kind=\"scatter\", c=cmap(float(i) / birds), s=dfgg[\"counts\"] * 5, ax=ax, label=bird, alpha=0.5)\n\nax.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=15, fancybox=True, shadow=True)\n\n# get axes limits\nx_lo, x_up = ax.get_xlim()\ny_lo, y_up = ax.get_ylim()\n# add minor ticks with a specified sapcing (deg)\ndeg = 5\n# add grid\nax.set_xticks(np.arange(np.ceil(x_lo), np.ceil(x_up), deg), minor=True)\nax.set_yticks(np.arange(np.ceil(y_lo), np.ceil(y_up), deg), minor=True)\nax.grid(b=True, which=\"minor\", alpha=0.25)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:48:50.421401Z","iopub.execute_input":"2022-05-24T22:48:50.421748Z","iopub.status.idle":"2022-05-24T22:49:06.724565Z","shell.execute_reply.started":"2022-05-24T22:48:50.421716Z","shell.execute_reply":"2022-05-24T22:49:06.723603Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* [@JIRKA BOROVEC/🦜BirdCLEF: world🌎map with birds](https://www.kaggle.com/jirkaborovec/birdclef-world-map-with-birds/)","metadata":{}},{"cell_type":"markdown","source":"==================================\n* I try plotly ,however this data that Skylark is not in Hawaii.","metadata":{}},{"cell_type":"code","source":"fig = px.scatter_geo(\n    train[train['primary_label'] == 'skylar'],\n    lat=\"latitude\",\n    lon=\"longitude\",\n    color=\"primary_label\",\n    width=1000,\n    height=500,\n    title=\"Skylak Distribution\",\n)\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:49:06.725748Z","iopub.execute_input":"2022-05-24T22:49:06.725989Z","iopub.status.idle":"2022-05-24T22:49:06.795123Z","shell.execute_reply.started":"2022-05-24T22:49:06.725956Z","shell.execute_reply":"2022-05-24T22:49:06.794468Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"==================================\n# Folium🗺","metadata":{}},{"cell_type":"code","source":"# folium\nbirdmap = folium.Map(\n    location = [19.629425,-155.361479], #  It's in Hawaii.\n    titles = 'BirdMap',\n    zoom_start = 7 \n) \n","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:49:06.796076Z","iopub.execute_input":"2022-05-24T22:49:06.796693Z","iopub.status.idle":"2022-05-24T22:49:06.802506Z","shell.execute_reply.started":"2022-05-24T22:49:06.796660Z","shell.execute_reply":"2022-05-24T22:49:06.801651Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for row in train_p.iterrows():\n    #base values\n    row_values = row[1] #this gets the \n    soundsrc = str(row_values['url']) + '/embed?simple=1' #this is the string part of the embed code...\n   \n    locations = [row_values['latitude'], row_values['longitude']]\n    \n    popup = '</iframe>' \\\n            f'<strong>  {row_values[\"common_name\"]}  </strong> \\\n            <br><br> \\\n            <strong> Location: </strong> {locations}  \\\n            <br><br> \\\n            <strong> Rating: </strong> {row_values[\"rating\"]} \\\n            <br><br> \\\n            This is a: <strong> {row_values[\"primary_label\"]} </strong>... Listen to it below. \\\n            <br><br> \\\n            <iframe src={soundsrc} scrolling=\"no\" frameborder=\"0\" width=\"340\" height=\"115\"></iframe>' \\\n            '</iframe>'\n    marker = folium.Marker(location=locations, popup = popup) #defines the marker\n    marker.add_to(birdmap) #adds the marker to the map\n    \nbirdmap","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:49:06.803873Z","iopub.execute_input":"2022-05-24T22:49:06.804628Z","iopub.status.idle":"2022-05-24T22:49:09.612001Z","shell.execute_reply.started":"2022-05-24T22:49:06.804581Z","shell.execute_reply":"2022-05-24T22:49:09.611064Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"This is it! I wanted to..\n*  [@ALEXIS COOK/Kaggle's courses /Geospatial Analysis 3/Interactive Maps](https://www.kaggle.com/alexisbcook/interactive-maps)\n* [@ALEX TEBOUL/Tutorial: BirdCLEF Visualizations with Plotly](https://www.kaggle.com/alexteboul/tutorial-birdclef-visualizations-with-plotly/)\n* [@ALEX TEBOUL/Tutorial: Play Bird Audio on Map with Folium](https://www.kaggle.com/alexteboul/tutorial-play-bird-audio-on-map-with-folium)","metadata":{}},{"cell_type":"markdown","source":"===================================\n# Audio▶","metadata":{}},{"cell_type":"code","source":"y, sr = librosa.load(f\"{BASE_DIR}train_audio/{fn}\")\nprint(f\"Numpy array of the audio loaded of shape {y.shape} and sample rate {sr}\")","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:49:09.613459Z","iopub.execute_input":"2022-05-24T22:49:09.613900Z","iopub.status.idle":"2022-05-24T22:49:11.072432Z","shell.execute_reply.started":"2022-05-24T22:49:09.613859Z","shell.execute_reply":"2022-05-24T22:49:11.071548Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"class configuraion():\n    '''Configuration File'''\n    n_fft = 2048\n    hop_length = n_fft // 4\n    \n    n_show_birds = 7\n    \nCFG = configuraion()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:49:11.073515Z","iopub.execute_input":"2022-05-24T22:49:11.073730Z","iopub.status.idle":"2022-05-24T22:49:11.079124Z","shell.execute_reply.started":"2022-05-24T22:49:11.073703Z","shell.execute_reply":"2022-05-24T22:49:11.078016Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df = train_p['primary_label'].value_counts().index\ndf","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:49:11.080684Z","iopub.execute_input":"2022-05-24T22:49:11.081367Z","iopub.status.idle":"2022-05-24T22:49:11.091238Z","shell.execute_reply.started":"2022-05-24T22:49:11.081321Z","shell.execute_reply":"2022-05-24T22:49:11.090660Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"\nfor i in df[:CFG.n_show_birds]:\n    print(i)\n    \n    path = train[train['primary_label'] == i].sample(1,random_state = 2022)['filename'].values[0]\n    path ='/kaggle/input/birdclef-2022/train_audio/' + path\n    \n    data, sample_rate = librosa.load(path)\n    \n    stft = librosa.stft(data, n_fft=CFG.n_fft, hop_length=CFG.hop_length)\n    spectrogram = np.abs(stft)\n    x = librosa.amplitude_to_db(spectrogram)\n    \n    \n    fig, ax = plt.subplots(ncols = 2, nrows = 1, figsize = (18,5))\n    \n    librosa.display.specshow(x, sr=sample_rate, hop_length=CFG.hop_length,ax = ax[0])\n    ax[0].set_xlabel(\"Time\")\n    ax[0].set_ylabel(\"Frequency\")\n    ax[0].set_title(\"Spectrogram\")\n    \n    librosa.display.waveshow(data,ax = ax[1])\n    plt.show()","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-05-24T22:49:11.092418Z","iopub.execute_input":"2022-05-24T22:49:11.093153Z","iopub.status.idle":"2022-05-24T22:49:49.241121Z","shell.execute_reply.started":"2022-05-24T22:49:11.093005Z","shell.execute_reply":"2022-05-24T22:49:49.240264Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Well, I don't know what to do next?\n* [@PAULO JUNQUEIRA/🐥 Little Bird, what sound is that? - EDA](https://www.kaggle.com/paulojunqueira/little-bird-what-sound-is-that-eda)","metadata":{}},{"cell_type":"markdown","source":"===================================\n# Noise reduction\n","metadata":{}},{"cell_type":"code","source":"test_soundscape = '../input/birdclef-2022/test_soundscapes/soundscape_453028782.ogg'\ny, sr = librosa.load(test_soundscape, sr=32000, offset=None)\nAudio(test_soundscape)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:49:49.242347Z","iopub.execute_input":"2022-05-24T22:49:49.242631Z","iopub.status.idle":"2022-05-24T22:49:49.325868Z","shell.execute_reply.started":"2022-05-24T22:49:49.242584Z","shell.execute_reply":"2022-05-24T22:49:49.325185Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(16, 8))\nsns.lineplot(x=np.arange(len(y)), y=y, ax=ax);","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:49:49.326873Z","iopub.execute_input":"2022-05-24T22:49:49.327686Z","iopub.status.idle":"2022-05-24T22:50:58.364289Z","shell.execute_reply.started":"2022-05-24T22:49:49.327645Z","shell.execute_reply":"2022-05-24T22:50:58.363398Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"reduced_noise = nr.reduce_noise(y=y, sr=32000)\nAudio(reduced_noise, rate=32000)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:50:58.365562Z","iopub.execute_input":"2022-05-24T22:50:58.366088Z","iopub.status.idle":"2022-05-24T22:50:59.442672Z","shell.execute_reply.started":"2022-05-24T22:50:58.366053Z","shell.execute_reply":"2022-05-24T22:50:59.441158Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y = reduced_noise\n\nfig, ax = plt.subplots(figsize=(16, 8))\nsns.lineplot(x=np.arange(len(y)), y=y, ax=ax)\n","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:50:59.444272Z","iopub.execute_input":"2022-05-24T22:50:59.445322Z","iopub.status.idle":"2022-05-24T22:52:08.600400Z","shell.execute_reply.started":"2022-05-24T22:50:59.445276Z","shell.execute_reply":"2022-05-24T22:52:08.599391Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* I will try spci.fft( Fast Fourier transform(FFT)) next time.\n* [@ZOLTAN KUCSIK//noisereduce package - Without Internet connection](https://www.kaggle.com/kucsikz/noisereduce-package-without-internet-connection/)","metadata":{}},{"cell_type":"markdown","source":"===================================\n# Submission","metadata":{}},{"cell_type":"code","source":"test_audio_dir = '../input/birdclef-2022/test_soundscapes/'\nfile_list = [f.split('.')[0] for f in sorted(os.listdir(test_audio_dir))]","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:52:08.601925Z","iopub.execute_input":"2022-05-24T22:52:08.602272Z","iopub.status.idle":"2022-05-24T22:52:08.608348Z","shell.execute_reply.started":"2022-05-24T22:52:08.602227Z","shell.execute_reply":"2022-05-24T22:52:08.607435Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#with open('../input/birdclef-2022/scored_birds.json') as sbfile:\n    #scored_birds = json.load(sbfile)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:52:08.610212Z","iopub.execute_input":"2022-05-24T22:52:08.610585Z","iopub.status.idle":"2022-05-24T22:52:08.620393Z","shell.execute_reply.started":"2022-05-24T22:52:08.610536Z","shell.execute_reply":"2022-05-24T22:52:08.619594Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"pred = {'row_id': [], 'target': []}\n\nfor afile in file_list:\n    \n    path = test_audio_dir + afile + '.ogg'\n    chunks = [[] for i in range(12)]\n    \n    for i in range(len(chunks)):        \n        chunk_end_time = (i + 1) * 5\n        for bird in scored_birds: # 21 Birds\n            \n            score = np.random.uniform()\n            \n            row_id = afile + '_' + bird + '_' + str(chunk_end_time)\n            \n            pred['row_id'].append(row_id)\n            pred['target'].append(True if score > 0.012 else False)","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:52:08.621892Z","iopub.execute_input":"2022-05-24T22:52:08.622354Z","iopub.status.idle":"2022-05-24T22:52:08.635554Z","shell.execute_reply.started":"2022-05-24T22:52:08.622250Z","shell.execute_reply":"2022-05-24T22:52:08.634519Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"results = pd.DataFrame(pred, columns = ['row_id', 'target'])\nresults.to_csv(\"submission.csv\", index=False)    \n","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:52:08.636787Z","iopub.execute_input":"2022-05-24T22:52:08.637041Z","iopub.status.idle":"2022-05-24T22:52:08.652627Z","shell.execute_reply.started":"2022-05-24T22:52:08.637011Z","shell.execute_reply":"2022-05-24T22:52:08.651846Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(results.head(50)) \nprint(results.tail(50))   ","metadata":{"execution":{"iopub.status.busy":"2022-05-24T22:52:08.653887Z","iopub.execute_input":"2022-05-24T22:52:08.654298Z","iopub.status.idle":"2022-05-24T22:52:08.674008Z","shell.execute_reply.started":"2022-05-24T22:52:08.654210Z","shell.execute_reply":"2022-05-24T22:52:08.673383Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"* This is the results before saving version_13. Why are the results displayed differently befor and after saving? I think that it could be a confusion.\n*                             row_id  target\n* 0     soundscape_453028782_akiapo_5    True\n* 1     soundscape_453028782_aniani_5   False\n* 2     soundscape_453028782_apapan_5    True\n* 3     soundscape_453028782_barpet_5    True\n* 4     soundscape_453028782_crehon_5   False\n* 5     soundscape_453028782_elepai_5    True\n* 6     soundscape_453028782_ercfra_5   False\n* 7     soundscape_453028782_hawama_5    True\n* 8     soundscape_453028782_hawcre_5   False\n* 9     soundscape_453028782_hawgoo_5    True\n* 10    soundscape_453028782_hawhaw_5    True\n* 11   soundscape_453028782_hawpet1_5    True\n* 12    soundscape_453028782_houfin_5    True\n* 13      soundscape_453028782_iiwi_5    True\n* 14    soundscape_453028782_jabwar_5    True\n* 15    soundscape_453028782_maupar_5    True\n* 16      soundscape_453028782_omao_5   False\n* 17    soundscape_453028782_puaioh_5   False\n* 18    soundscape_453028782_skylar_5   False\n* 19   soundscape_453028782_warwhe1_5    True\n* 20    soundscape_453028782_yefcan_5    True\n* 21   soundscape_453028782_akiapo_10    True\n* 22   soundscape_453028782_aniani_10    True\n* 23   soundscape_453028782_apapan_10    True\n* 24   soundscape_453028782_barpet_10   False\n* 25   soundscape_453028782_crehon_10   False\n* 26   soundscape_453028782_elepai_10   False\n* 27   soundscape_453028782_ercfra_10    True\n* 28   soundscape_453028782_hawama_10    True\n* 29   soundscape_453028782_hawcre_10    True\n* 30   soundscape_453028782_hawgoo_10    True\n* 31   soundscape_453028782_hawhaw_10    True\n* 32  soundscape_453028782_hawpet1_10   False\n* 33   soundscape_453028782_houfin_10   False\n* 34     soundscape_453028782_iiwi_10    True\n* 35   soundscape_453028782_jabwar_10    True\n* 36   soundscape_453028782_maupar_10   False\n* 37     soundscape_453028782_omao_10    True\n* 38   soundscape_453028782_puaioh_10   False\n* 39   soundscape_453028782_skylar_10   False\n* 40  soundscape_453028782_warwhe1_10   False\n* 41   soundscape_453028782_yefcan_10   False\n* 42   soundscape_453028782_akiapo_15   False\n* 43   soundscape_453028782_aniani_15    True\n* 44   soundscape_453028782_apapan_15    True\n* 45   soundscape_453028782_barpet_15   False\n* 46   soundscape_453028782_crehon_15    True\n* 47   soundscape_453028782_elepai_15   False\n* 48   soundscape_453028782_ercfra_15    True\n* 49   soundscape_453028782_hawama_15    True\n*                               row_id  target\n* 202     soundscape_453028782_iiwi_50   False\n* 203   soundscape_453028782_jabwar_50   False\n* 204   soundscape_453028782_maupar_50   False\n* 205     soundscape_453028782_omao_50   False\n* 206   soundscape_453028782_puaioh_50    True\n* 207   soundscape_453028782_skylar_50    True\n* 208  soundscape_453028782_warwhe1_50    True\n* 209   soundscape_453028782_yefcan_50   False\n* 210   soundscape_453028782_akiapo_55   False\n* 211   soundscape_453028782_aniani_55    True\n* 212   soundscape_453028782_apapan_55   False\n* 213   soundscape_453028782_barpet_55   False\n* 214   soundscape_453028782_crehon_55    True\n* 215   soundscape_453028782_elepai_55   False\n* 216   soundscape_453028782_ercfra_55    True\n* 217   soundscape_453028782_hawama_55    True\n* 218   soundscape_453028782_hawcre_55   False\n* 219   soundscape_453028782_hawgoo_55    True\n* 220   soundscape_453028782_hawhaw_55    True\n* 221  soundscape_453028782_hawpet1_55    True\n* 222   soundscape_453028782_houfin_55    True\n* 223     soundscape_453028782_iiwi_55   False\n* 224   soundscape_453028782_jabwar_55   False\n* 225   soundscape_453028782_maupar_55   False\n* 226     soundscape_453028782_omao_55    True\n* 227   soundscape_453028782_puaioh_55   False\n* 228   soundscape_453028782_skylar_55    True\n* 229  soundscape_453028782_warwhe1_55   False\n* 230   soundscape_453028782_yefcan_55    True\n* 231   soundscape_453028782_akiapo_60   False\n* 232   soundscape_453028782_aniani_60   False\n* 233   soundscape_453028782_apapan_60   False\n* 234   soundscape_453028782_barpet_60   False\n* 235   soundscape_453028782_crehon_60   False\n* 236   soundscape_453028782_elepai_60    True\n* 237   soundscape_453028782_ercfra_60    True\n* 238   soundscape_453028782_hawama_60   False\n* 239   soundscape_453028782_hawcre_60   False\n* 240   soundscape_453028782_hawgoo_60   False\n* 241   soundscape_453028782_hawhaw_60   False\n* 242  soundscape_453028782_hawpet1_60   False\n* 243   soundscape_453028782_houfin_60    True\n* 244     soundscape_453028782_iiwi_60    True\n* 245   soundscape_453028782_jabwar_60   False\n* 246   soundscape_453028782_maupar_60   False\n* 247     soundscape_453028782_omao_60    True\n* 248   soundscape_453028782_puaioh_60   False\n* 249   soundscape_453028782_skylar_60    True\n* 250  soundscape_453028782_warwhe1_60   False\n* 251   soundscape_453028782_yefcan_60    True","metadata":{}},{"cell_type":"markdown","source":"* The results will vary each time.\n* I have to improve.💪\n* [@STEFAN KAHL](https://www.kaggle.com/stefankahl/how-to-submit-to-birdclef-2022/)\n","metadata":{}},{"cell_type":"markdown","source":"==================================\n* It's a mish_mash, but I learned a lot of things.\n* Please don't forget to upvote them! Thank you all!\n> # In progress..........","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}