\n\n
💡 About The Competition :
\n \n**Objective**: The competition aims to advance biodiversity monitoring efforts in the Western Ghats, a Global Biodiversity Hotspot in India, by leveraging machine learning techniques to identify under-studied Indian bird species through their calls.\n\n**Dataset**: Participants are provided with a dataset consisting of audio recordings of bird calls from the Western Ghats region, along with associated metadata such as species labels, geographic coordinates, and recording details. Additionally, there are test soundscapes and unlabeled audio data for evaluation.\n\n**Task**: Participants are tasked with developing computational solutions to process the audio data and accurately classify bird species present in the recordings. The competition focuses on identifying endemic species, detecting endangered species with limited training data, and classifying poorly understood nocturnal species.\n\n**Collaborators**: The competition is collaboratively organized by various institutions including the Chemnitz University of Technology, Google Research, Indian Institute of Science Education and Research (IISER) Tirupati, K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology, LifeCLEF, and Xeno-canto.\n\n**Significance**: Successful solutions developed in the competition will contribute to more comprehensive and efficient monitoring of avian populations in the Western Ghats. This, in turn, will aid conservation efforts by providing insights into biodiversity trends and informing targeted conservation actions.","metadata":{}},{"cell_type":"markdown","source":"
\n
Importing Libraries
\n \n","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport librosa.display\nimport IPython.display as ipd\nimport squarify","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:36.042928Z","iopub.execute_input":"2024-06-10T15:28:36.043332Z","iopub.status.idle":"2024-06-10T15:28:37.794500Z","shell.execute_reply.started":"2024-06-10T15:28:36.043298Z","shell.execute_reply":"2024-06-10T15:28:37.793374Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_sub = pd.read_csv('/kaggle/input/birdclef-2024/sample_submission.csv')\ndf_train = pd.read_csv('/kaggle/input/birdclef-2024/train_metadata.csv')\ndf_t = pd.read_csv('/kaggle/input/birdclef-2024/eBird_Taxonomy_v2021.csv')","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:37.796859Z","iopub.execute_input":"2024-06-10T15:28:37.797314Z","iopub.status.idle":"2024-06-10T15:28:38.084643Z","shell.execute_reply.started":"2024-06-10T15:28:37.797274Z","shell.execute_reply":"2024-06-10T15:28:38.083383Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train.head()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:38.086252Z","iopub.execute_input":"2024-06-10T15:28:38.086604Z","iopub.status.idle":"2024-06-10T15:28:38.119947Z","shell.execute_reply.started":"2024-06-10T15:28:38.086572Z","shell.execute_reply":"2024-06-10T15:28:38.118825Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train.dtypes","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:38.123013Z","iopub.execute_input":"2024-06-10T15:28:38.123515Z","iopub.status.idle":"2024-06-10T15:28:38.132907Z","shell.execute_reply.started":"2024-06-10T15:28:38.123441Z","shell.execute_reply":"2024-06-10T15:28:38.131559Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_sub.head()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:38.134397Z","iopub.execute_input":"2024-06-10T15:28:38.134797Z","iopub.status.idle":"2024-06-10T15:28:38.167262Z","shell.execute_reply.started":"2024-06-10T15:28:38.134761Z","shell.execute_reply":"2024-06-10T15:28:38.165846Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_t.head()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:38.168996Z","iopub.execute_input":"2024-06-10T15:28:38.169409Z","iopub.status.idle":"2024-06-10T15:28:38.191422Z","shell.execute_reply.started":"2024-06-10T15:28:38.169366Z","shell.execute_reply":"2024-06-10T15:28:38.190151Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"file_path = \"/kaggle/input/birdclef-2024/train_audio/asbfly/XC134896.ogg\"\naudio_data, sample_rate = librosa.load(file_path)\nprint(\"Audio data shape:\", audio_data.shape)\nprint(\"Sample rate:\", sample_rate)","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:38.192843Z","iopub.execute_input":"2024-06-10T15:28:38.193206Z","iopub.status.idle":"2024-06-10T15:28:50.630064Z","shell.execute_reply.started":"2024-06-10T15:28:38.193166Z","shell.execute_reply":"2024-06-10T15:28:50.628745Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(14, 5))\nplt.plot(audio_data)\nplt.xlabel('Time (samples)')\nplt.ylabel('Amplitude')\nplt.title('Waveform')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:50.631511Z","iopub.execute_input":"2024-06-10T15:28:50.632204Z","iopub.status.idle":"2024-06-10T15:28:51.101762Z","shell.execute_reply.started":"2024-06-10T15:28:50.632168Z","shell.execute_reply":"2024-06-10T15:28:51.100360Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"mfccs = librosa.feature.mfcc(y=audio_data, sr=sample_rate, n_mfcc=13)\nplt.figure(figsize=(10, 4))\nlibrosa.display.specshow(mfccs, sr=sample_rate, x_axis='time')\nplt.colorbar()\nplt.title('MFCCs')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:51.103241Z","iopub.execute_input":"2024-06-10T15:28:51.103703Z","iopub.status.idle":"2024-06-10T15:28:52.786461Z","shell.execute_reply.started":"2024-06-10T15:28:51.103638Z","shell.execute_reply":"2024-06-10T15:28:52.785200Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"chroma = librosa.feature.chroma_stft(y=audio_data, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nlibrosa.display.specshow(chroma, sr=sample_rate, x_axis='time', y_axis='chroma')\nplt.colorbar()\nplt.title('Chromagram')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:52.790663Z","iopub.execute_input":"2024-06-10T15:28:52.791090Z","iopub.status.idle":"2024-06-10T15:28:53.836126Z","shell.execute_reply.started":"2024-06-10T15:28:52.791055Z","shell.execute_reply":"2024-06-10T15:28:53.835063Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"energy = librosa.feature.rms(y=audio_data)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(energy), energy[0])\nplt.xlabel('Time (s)')\nplt.ylabel('Energy')\nplt.title('Energy Plot')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:53.837499Z","iopub.execute_input":"2024-06-10T15:28:53.837847Z","iopub.status.idle":"2024-06-10T15:28:54.146213Z","shell.execute_reply.started":"2024-06-10T15:28:53.837818Z","shell.execute_reply":"2024-06-10T15:28:54.144767Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"zero_crossings = librosa.feature.zero_crossing_rate(y=audio_data)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(zero_crossings), zero_crossings[0])\nplt.xlabel('Time (s)')\nplt.ylabel('Zero-Crossing Rate')\nplt.title('Zero-Crossing Rate Plot')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:54.147879Z","iopub.execute_input":"2024-06-10T15:28:54.148351Z","iopub.status.idle":"2024-06-10T15:28:54.433100Z","shell.execute_reply.started":"2024-06-10T15:28:54.148308Z","shell.execute_reply":"2024-06-10T15:28:54.431764Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tempo, beat_frames = librosa.beat.beat_track(y=audio_data, sr=sample_rate)\nbeat_times = librosa.frames_to_time(beat_frames, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(audio_data), audio_data)\nplt.vlines(beat_times, -1, 1, color='r', linestyle='--', alpha=0.5, label='Beats')\nplt.xlabel('Time (s)')\nplt.ylabel('Amplitude')\nplt.title('Beat Tracking Plot')\nplt.legend()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:54.434505Z","iopub.execute_input":"2024-06-10T15:28:54.435451Z","iopub.status.idle":"2024-06-10T15:28:55.465805Z","shell.execute_reply.started":"2024-06-10T15:28:54.435399Z","shell.execute_reply":"2024-06-10T15:28:55.464549Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tempogram = librosa.feature.tempogram(y=audio_data, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nlibrosa.display.specshow(tempogram, sr=sample_rate, x_axis='time', y_axis='tempo')\nplt.colorbar()\nplt.title('Tempogram Plot')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:55.467993Z","iopub.execute_input":"2024-06-10T15:28:55.468418Z","iopub.status.idle":"2024-06-10T15:28:56.256079Z","shell.execute_reply.started":"2024-06-10T15:28:55.468379Z","shell.execute_reply":"2024-06-10T15:28:56.254952Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"spectral_rolloff = librosa.feature.spectral_rolloff(y=audio_data, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(spectral_rolloff), spectral_rolloff[0])\nplt.xlabel('Time (s)')\nplt.ylabel('Spectral Rolloff')\nplt.title('Spectral Rolloff Plot')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:56.257320Z","iopub.execute_input":"2024-06-10T15:28:56.257653Z","iopub.status.idle":"2024-06-10T15:28:56.571366Z","shell.execute_reply.started":"2024-06-10T15:28:56.257624Z","shell.execute_reply":"2024-06-10T15:28:56.570186Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"harmonic = librosa.effects.harmonic(y=audio_data)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(harmonic), harmonic)\nplt.xlabel('Time (s)')\nplt.ylabel('Amplitude')\nplt.title('Harmonic Content Plot')\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:28:56.572874Z","iopub.execute_input":"2024-06-10T15:28:56.573207Z","iopub.status.idle":"2024-06-10T15:29:00.038765Z","shell.execute_reply.started":"2024-06-10T15:28:56.573178Z","shell.execute_reply":"2024-06-10T15:29:00.037564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"spectral_flatness = librosa.feature.spectral_flatness(y=audio_data)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(spectral_flatness), spectral_flatness[0])\nplt.xlabel('Time (s)')\nplt.ylabel('Spectral Flatness')\nplt.title('Spectral Flatness Plot')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:00.040097Z","iopub.execute_input":"2024-06-10T15:29:00.040438Z","iopub.status.idle":"2024-06-10T15:29:00.314048Z","shell.execute_reply.started":"2024-06-10T15:29:00.040399Z","shell.execute_reply":"2024-06-10T15:29:00.312553Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"f0, voiced_flag, voiced_probs = librosa.pyin(y=audio_data, fmin=librosa.note_to_hz('C2'), fmax=librosa.note_to_hz('C7'))\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(f0), f0)\nplt.xlabel('Time (s)')\nplt.ylabel('Frequency (Hz)')\nplt.title('Pitch Contour')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:00.315729Z","iopub.execute_input":"2024-06-10T15:29:00.316176Z","iopub.status.idle":"2024-06-10T15:29:12.745730Z","shell.execute_reply.started":"2024-06-10T15:29:00.316134Z","shell.execute_reply":"2024-06-10T15:29:12.744660Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"spectral_centroids = librosa.feature.spectral_centroid(y=audio_data, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nplt.plot(librosa.times_like(spectral_centroids), spectral_centroids[0])\nplt.xlabel('Time (s)')\nplt.ylabel('Spectral Centroid')\nplt.title('Spectral Centroid Plot')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:12.747203Z","iopub.execute_input":"2024-06-10T15:29:12.747555Z","iopub.status.idle":"2024-06-10T15:29:13.084200Z","shell.execute_reply.started":"2024-06-10T15:29:12.747524Z","shell.execute_reply":"2024-06-10T15:29:13.083088Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"spectral_contrast = librosa.feature.spectral_contrast(y=audio_data, sr=sample_rate)\nplt.figure(figsize=(10, 4))\nlibrosa.display.specshow(spectral_contrast, sr=sample_rate, x_axis='time')\nplt.colorbar()\nplt.title('Spectral Contrast Plot')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:13.085823Z","iopub.execute_input":"2024-06-10T15:29:13.086219Z","iopub.status.idle":"2024-06-10T15:29:13.446815Z","shell.execute_reply.started":"2024-06-10T15:29:13.086185Z","shell.execute_reply":"2024-06-10T15:29:13.445613Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(20, 26))\nsns.countplot(data=df_train, y='primary_label', order=df_train['primary_label'].value_counts().index)\nplt.title('Distribution of Primary Labels')\nplt.xlabel('Count')\nplt.ylabel('Primary Label')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:13.448143Z","iopub.execute_input":"2024-06-10T15:29:13.448465Z","iopub.status.idle":"2024-06-10T15:29:15.835045Z","shell.execute_reply.started":"2024-06-10T15:29:13.448436Z","shell.execute_reply":"2024-06-10T15:29:15.833655Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"","metadata":{},"attachments":{"aad579e0-b0d6-405b-abd2-05b10f06a2bf.jpg":{"image/jpeg":"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= \"/kaggle/input/birdclef-2024/train_audio/ashpri1/XC116338.ogg\"\n\nipd.display(ipd.Audio(SOUND_DIR))\n\n\nsignal, sr = librosa.load(SOUND_DIR, duration=10)\n\n\nplt.figure(figsize=(10, 4))\nlibrosa.display.waveshow(signal, sr=sr)\nplt.title(\"Monophonic\")\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:15.837165Z","iopub.execute_input":"2024-06-10T15:29:15.837569Z","iopub.status.idle":"2024-06-10T15:29:16.407794Z","shell.execute_reply.started":"2024-06-10T15:29:15.837532Z","shell.execute_reply":"2024-06-10T15:29:16.406742Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def plot_spectrogram(signal, sr, feature='linear', fmin=0, fmax=None):\n \n if feature == 'linear':\n D = librosa.amplitude_to_db(np.abs(librosa.stft(signal)), ref=np.max)\n elif feature == 'mel':\n S = librosa.feature.melspectrogram(\n y=signal,\n sr=sr,\n n_fft=N_FFT,\n hop_length=HOP_SIZE,\n n_mels=N_MELS,\n htk=True,\n fmin=fmin,\n fmax=fmax,\n )\n D = librosa.power_to_db(S ** 2, ref=np.max)\n\n \n plt.figure(figsize=(10, 4))\n librosa.display.specshow(D, fmin=fmin, y_axis=\"linear\")\n plt.colorbar(format=\"%+2.0f dB\")\n plt.title(f\"{feature.capitalize()}-scaled spectrogram\")\n plt.show()\n\nSOUND_DIR = \"/kaggle/input/birdclef-2024/train_audio/asbfly/XC134896.ogg\"\nsignal, sr = librosa.load(SOUND_DIR, duration=10)\n\nplot_spectrogram(signal, sr, feature='linear')","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:16.409323Z","iopub.execute_input":"2024-06-10T15:29:16.409785Z","iopub.status.idle":"2024-06-10T15:29:17.089403Z","shell.execute_reply.started":"2024-06-10T15:29:16.409745Z","shell.execute_reply":"2024-06-10T15:29:17.088209Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(8, 6))\nsns.histplot(data=df_train, x='rating', bins=20, kde=True)\nplt.title('Distribution of Ratings')\nplt.xlabel('Rating')\nplt.ylabel('Frequency')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:17.090880Z","iopub.execute_input":"2024-06-10T15:29:17.091207Z","iopub.status.idle":"2024-06-10T15:29:17.582271Z","shell.execute_reply.started":"2024-06-10T15:29:17.091180Z","shell.execute_reply":"2024-06-10T15:29:17.581014Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.set(rc={'figure.figsize':(20,10)})\nsns.countplot(x='rating', data=df_train, edgecolor=(0,0,0), linewidth=2, palette=('cubehelix'))","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:17.583877Z","iopub.execute_input":"2024-06-10T15:29:17.584359Z","iopub.status.idle":"2024-06-10T15:29:18.063082Z","shell.execute_reply.started":"2024-06-10T15:29:17.584315Z","shell.execute_reply":"2024-06-10T15:29:18.061921Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import plotly.graph_objects as go\n\n# Create a scattermapbox plot\nfig = go.Figure(go.Scattermapbox(\n lat=df_train['latitude'], \n lon=df_train['longitude'],\n mode='markers',\n marker=go.scattermapbox.Marker(\n size=9,\n color='rgb(255, 0, 0)',\n opacity=0.5\n ),\n text='Recordings'\n))\n\n# Customize layout\nfig.update_layout(\n mapbox=dict(\n style=\"open-street-map\", # You can change the map style here\n center=dict(lon=df_train['longitude'].median(), lat=df_train['latitude'].median()),\n zoom=5 # Adjust the zoom level as needed\n ),\n margin=dict(l=0, r=0, t=0, b=0),\n title='Geographic Distribution of Recordings'\n)\n\nfig.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:18.064599Z","iopub.execute_input":"2024-06-10T15:29:18.064981Z","iopub.status.idle":"2024-06-10T15:29:18.461487Z","shell.execute_reply.started":"2024-06-10T15:29:18.064947Z","shell.execute_reply":"2024-06-10T15:29:18.460418Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(10, 8))\nsns.scatterplot(data=df_train, x='longitude', y='latitude', alpha=0.5)\nplt.title('Geographic Distribution of Recordings')\nplt.xlabel('Longitude')\nplt.ylabel('Latitude')\nplt.legend(bbox_to_anchor=(1.05, 1), loc='upper left')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:18.463021Z","iopub.execute_input":"2024-06-10T15:29:18.463413Z","iopub.status.idle":"2024-06-10T15:29:18.897328Z","shell.execute_reply.started":"2024-06-10T15:29:18.463379Z","shell.execute_reply":"2024-06-10T15:29:18.896247Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt.figure(figsize=(12, 6))\nsns.countplot(data=df_train, y='author', order=df_train['author'].value_counts().index[:10])\nplt.title('Distribution of Recordings by Author (Top 10)')\nplt.xlabel('Count')\nplt.ylabel('Author')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:18.901831Z","iopub.execute_input":"2024-06-10T15:29:18.902183Z","iopub.status.idle":"2024-06-10T15:29:19.248883Z","shell.execute_reply.started":"2024-06-10T15:29:18.902153Z","shell.execute_reply":"2024-06-10T15:29:19.247697Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train.columns","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:19.250507Z","iopub.execute_input":"2024-06-10T15:29:19.250977Z","iopub.status.idle":"2024-06-10T15:29:19.258972Z","shell.execute_reply.started":"2024-06-10T15:29:19.250937Z","shell.execute_reply":"2024-06-10T15:29:19.257798Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from wordcloud import WordCloud\n\nwordcloud = WordCloud(width=800, height=400, background_color='white').generate(' '.join(df_train['primary_label']))\n\n# Plot the word cloud\nplt.figure(figsize=(10, 8))\nplt.imshow(wordcloud, interpolation='bilinear')\nplt.title('Primary Label Word Cloud')\nplt.axis('off')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:19.260327Z","iopub.execute_input":"2024-06-10T15:29:19.260662Z","iopub.status.idle":"2024-06-10T15:29:20.750346Z","shell.execute_reply.started":"2024-06-10T15:29:19.260628Z","shell.execute_reply":"2024-06-10T15:29:20.749220Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train.columns","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:20.751548Z","iopub.execute_input":"2024-06-10T15:29:20.751876Z","iopub.status.idle":"2024-06-10T15:29:20.759324Z","shell.execute_reply.started":"2024-06-10T15:29:20.751848Z","shell.execute_reply":"2024-06-10T15:29:20.758217Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_train.dtypes","metadata":{"execution":{"iopub.status.busy":"2024-06-10T15:29:20.760625Z","iopub.execute_input":"2024-06-10T15:29:20.760994Z","iopub.status.idle":"2024-06-10T15:29:20.781024Z","shell.execute_reply.started":"2024-06-10T15:29:20.760964Z","shell.execute_reply":"2024-06-10T15:29:20.779258Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"
\n\n
💡 Observation from above plot :
\n \n\n \n WIP\n","metadata":{}},{"cell_type":"markdown","source":"
\n
Looking Forward for feeback
\n 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"}}},{"cell_type":"markdown","source":"For Categorical plots please refer https://chartexpo.com/blog/best-graphs-for-categorical-data#\n\nRefrences https://github.com/AgaMiko/bird-recognition-review?tab=readme-ov-file#Competitions","metadata":{}},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}