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01 Financial Analysis - Basic Evaluation Metrics
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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) | |
import matplotlib.pyplot as plt # Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy | |
import matplotlib.patches as mpatches | |
import pprint # Pretty printer | |
# 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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