D-32-데이터분석

1. A if 조건 else B

df['Real-Sale'] = A if 1 is 0 else B

2. value_counts()

df['Ship Mode'].value_counts()

3. DataFrame()

df=pd.DataFrame(df.groupby('State')['Profit'].sum().sort_values(ascending=False)).reset_index()

4. pd.merge()

df_merge = pd.merge(df_profit_sum, df_realSale_sum, how='left', on='State')

df_Sale = pd.DataFrame({'Sub-Category':list(df.groupby('Sub-Category')['Real-Sale'].sum().index),
                        "Real-Sales":list(df.groupby('Sub-Category')['Real-Sale'].sum())})

5. plt.plot
   

import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use(['dark_background'])

plt.plot(df_State_Sale_Profit['State'],df_State_Sale_Profit['Profit'], label='Profit')
plt.gcf().set_size_inches(25,8)

plt.plot(df_State_Sale_Profit['State'],df_State_Sale_Profit['Real-Sale'], label='Sale')
plt.gcf().set_size_inches(25,8)

plt.xticks(rotation=45)
plt.legend()

6. sns.barplot
   

import matplotlib.pyplot as plt
import seaborn as sns

li_order = list(df_merge.sort_values(by=['Profit'], ascending = False)['Sub-Category'])

custom_palette = sns.color_palette("Paired")
sns.set(style="darkgrid")

plt.figure(figsize=(30, 15))
ax = plt.gca()

plt.subplot(3, 1, 1)
sns.barplot(x='Sub-Category', y='Profit', data=df_merge, palette=custom_palette, order=li_order)
plt.ylabel('Profit')

plt.subplot(3, 1, 2)
sns.barplot(x='Sub-Category', y='count', data=df_merge,palette=custom_palette,order=li_order)
plt.ylabel('Count')

plt.subplot(3, 1, 3)
sns.barplot(x='Sub-Category', y='Real-Sales', data=df_merge,palette=custom_palette,order=li_order)
plt.xlabel('Sub Categories')
plt.ylabel('Sales')

plt.show()

7. unique()

li_cate = []
for c in li_sub:
  li_cate.append(str(df[df['Sub-Category']==c]['Category'].unique()))
li_cate

["['Technology']",
"['Technology']",
"['Technology']",
"['Office Supplies']",
"['Office Supplies']",
"['Furniture']",
"['Office Supplies']",
"['Office Supplies']",
"['Furniture']"]