扩展与操作数据

Python 金融进阶

Kennedy Behrman

Data Engineer, Author, Founder

PCE

个人消费支出（PCE）

PCE =

PCE

个人消费支出（PCE）

PCE = PCDG

耐用品

A Stove

¹ 作者 cactus cowboy ² Open Clipart，CC0，https://commons.wikimedia.org/w/index.php?curid=64953673

PCE

个人消费支出（PCE）

PCE = PCDG + PCNDG

非耐用品

Pineapple

¹ 作者 Smart Servier ² https://smart.servier.com/，CC BY 3.0，https://commons.wikimedia.org/w/index.php?curid=74765623

PCE

个人消费支出（PCE）

PCE = PCDG + PCNDG + PCESV

服务

Man with clipboard

¹ 作者 Clip Art by Vector Toons ² 自制作品，CC BY-SA 4.0，https://commons.wikimedia.org/w/index.php?curid=65937611

PCE - 添加与删除列

DATE	PCDGA
1929-01-01	9.829
1930-01-01	7.661
1931-01-01	5.911
1932-01-01	3.959

PCE - 添加与删除列

pce['PCND'] = [[33.941,
                30.503,
                25.798000000000002,
                20.169]

PCE - 添加与删除列

pce

DATE	PCDG	PCND
1929-01-01	9.829	33.941
1930-01-01	7.661	30.503
1931-01-01	5.911	25.798
1932-01-01	3.959	20.169

PCE - 添加与删除列

pce

DATE	PCDG	PCND
1929-01-01	9.829	33.941
1930-01-01	7.661	30.503
1931-01-01	5.911	25.798
1932-01-01	3.959	20.169

pcesv

PCESV
0	33.613
1	31.972
2	28.963
3	24.587

PCE - 添加与删除列

pce['PCESV'] = pcesv

pce

PCE - 添加与删除列

pce['PCESV'] = pcesv

pce

DATE	PCDG	PCND	PCESV
1929-01-01	9.829	33.941	33.613
1930-01-01	7.661	30.503	31.972
1931-01-01	5.911	25.798	28.963
1932-01-01	3.959	20.169	24.587

PCE - 添加与删除列

pce['PCE'] = pce['PCDG'] + pce['PCND'] + pce['PCESV']

PCE - 添加与删除列

pce['PCE'] = pce['PCDG'] + pce['PCND'] + pce['PCESV']

DATE	PCDG	PCND	PCESV	PCE
1929-01-01	9.829	33.941	33.613	77.383
1930-01-01	7.661	30.503	31.972	70.136
1931-01-01	5.911	25.798	28.963	60.672
1932-01-01	3.959	20.169	24.587	48.715

PCE - 添加与删除列

pce.drop(columns=['PCDG', 'PCND', 'PCESV'], 
         axis=1, 
         inplace=True)

PCE - 添加与删除列

pce.drop(columns=['PCDG', 'PCND', 'PCESV'], 
         axis=1, 
         inplace=True)

DATE	PCE
1929-01-01	77.383
1930-01-01	70.136
1931-01-01	60.672
1932-01-01	48.715

PCE - 添加与删除行

new_row

PCE - 添加与删除行

new_row

DATE	PCE
1933-01-01	45.945

pce.append(new_row)

PCE - 添加与删除行

new_row

DATE	PCE
1933-01-01	45.945

pce.append(new_row)

DATE	PCE
1929-01-01	77.383
1930-01-01	70.136
1931-01-01	60.672
1932-01-01	48.715
1933-01-01	45.945

PCE - 添加与删除行

添加多行

new_rows = [ row1, row2, row3
]
for row in new_rows:
    pce = pce.append(row)

PCE - 添加与删除行

添加多行

for row in new_rows:
    pce = pce.append(row)

DATE	PCE
1929-01-01	77.383
1930-01-01	70.136
1931-01-01	60.672
1932-01-01	48.715
1933-01-01	45.945
1934-01-01	51.461
1935-01-01	55.933

PCE - 添加与删除行

pce.drop(['1934-01-01',
          '1935-01-01',
          '1936-01-01',
          '1937-01-01',
          '1938-01-01',
          '1939-01-01'], 
          inplace=True)

PCE - 添加与删除行

pce.drop(['1934-01-01',
          '1935-01-01',
          '1936-01-01',
          '1937-01-01',
          '1938-01-01',
          '1939-01-01'], 
          inplace=True)

DATE	PCE
1929-01-01	77.383
1930-01-01	70.136
1931-01-01	60.672
1932-01-01	48.715
1933-01-01	45.945

PCE - 添加与删除行

all_rows = [row1, row2, row3, pce]

pd.concat(all_rows)

PCE - 添加与删除行

all_rows = [row1, row2, row3, pce]

pd.concat(all_rows)

DATE	PCE
1929-01-01	77.383
1930-01-01	70.136
1931-01-01	60.672
1932-01-01	48.715
1933-01-01	45.945
1934-01-01	51.461
1935-01-01	55.933

PCE - 对 DataFrame 进行运算

ec = 0.88
pce * ec

PCE - 对 DataFrame 进行运算

ec = 0.88
pce * ec

DATE	PCE
1934-01-01	45.28568
1935-01-01	49.22104
1936-01-01	54.72544
1937-01-01	58.81832

PCE - map

def convert_to_euro(x):
    return x * 0.88

pce['EURO'] = pce['PCE'].map(convert_to_euro)

PCE - map

def convert_to_euro(x):
    return x * 0.88

pce['EURO'] = pce['PCE'].map(convert_to_euro)

DATE	PCE	EURO
1934-01-01	51.461	45.28568
1935-01-01	55.933	49.22104
1936-01-01	62.188	54.72544

国内生产总值（GDP）

GDP = PCE + GE + GPDI + NE
PCE：个人消费支出
GE：政府支出
GPDI：私人国内总投资
NE：净出口

GDP - apply

map - 列（Series）中的元素

apply - 跨行或列

GDP - apply

	GCE	GPDI	NE	PCE
DATE
1929-01-01	9.622	17.170	0.383	77.383
1930-01-01	10.273	11.428	0.323	70.136
1931-01-01	10.169	6.549	0.001	60.672
1932-01-01	8.946	1.819	0.043	48.715

GDP - apply

gdp.apply(np.sum, axis=1)

GDP - apply

gdp['GDP'] = gdp.apply(np.sum, axis=1)

	GCE	GPDI	NE	PCE	GDP
DATE
1929-01-01	9.622	17.170	0.383	77.383	104.558
1930-01-01	10.273	11.428	0.323	70.136	92.160
1931-01-01	10.169	6.549	0.001	60.672	77.391
1932-01-01	8.946	1.819	0.043	48.715	59.523

Vamos praticar!

Python 金融进阶