<jupyter_start><jupyter_text>Vietnamese Financial Report DataThis notebook is provided as a demo for how to use the data.<jupyter_code>import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
import os<jupyter_output><empty_output><jupyter_text>Display config<jupyter_code>def format_float(float_num):
    return '{:,.2f}'.format(float_num).replace(',', ' ')
pd.set_option('max_colwidth', None)
pd.set_option('max_rows', None)
pd.set_option('float_format', format_float)<jupyter_output><empty_output><jupyter_text>Load data<jupyter_code>BALANCE_SHEET_PATH = os.path.join('data', 'Balance Sheet', 'csv')

bs4 = pd.read_csv(os.path.join(BALANCE_SHEET_PATH, 'Q4 2021.csv'), encoding='utf8', index_col='ID')
bs4.head()
print(bs4.index)
bs4.columns<jupyter_output><empty_output><jupyter_text>Balance sheet of a specific company (AAA)<jupyter_code>bs_aaa = bs4['AAA'].dropna()
bs_aaa.reset_index()<jupyter_output><empty_output><jupyter_text>Transpose dataIn many cases, you'll want to use sections in the balance sheet as features. In those circumtances, you might need to transpose data.In this example, we will plot top 10 companies that have the highest `TỔNG CỘNG NGUỒN VỐN`<jupyter_code>t_bs4 = bs4.T
t_bs4.head()
top10 = t_bs4['TỔNG CỘNG NGUỒN VỐN'].nlargest(10)
top10
plt.figure(figsize=(15, 8))
sns.barplot(x=top10.index, y=top10, palette="Blues_d")
plt.show()<jupyter_output><empty_output>
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