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# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session
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project_name = "zerotopandas-course-project-Pokemon"
!pip install jovian --upgrade -q
WARNING: You are using pip version 20.2.2; however, version 20.2.3 is available. You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.
In [2]:
import jovian
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jovian.commit(project= "zerotopandas-course-project-Pokemon")
[jovian] Attempting to save notebook.. [jovian] Detected Kaggle notebook... [jovian] Please enter your API key ( from https://jovian.ml/ ): API KEY: ········ [jovian] Uploading notebook to https://jovian.ml/multiplexpcr/zerotopandas-course-project-Pokemon