我有以下示例資料：
rec.array([('FY20', 361.410592 , nan, 21.97, nan, 'Total', 'Fast'),
('FY21', 359.26952604, -1., 22.99, 5., 'Total', 'Fast'),
('FY22', 362.4560529 , 1., 22.77, -1., 'Total', 'Fast'),
('FY23', 371.53543252, 2., 21.92, -4., 'Total', 'Fast'),
('FY24', 374.48894494, 1., 21.88, -0., 'Total', 'Fast'),
('FY25', 377.09481613, 1., 21.85, -0., 'Total', 'Fast'),
('FY20', 67.043756 , nan, 21. , nan, 'Homes', 'Fast'),
('FY21', 110.12145222, 63., 20.95, -0., 'Homes', 'Fast'),
('FY22', 117.46526727, 7., 20.73, -1., 'Homes', 'Fast'),
('FY23', 125.83482531, 7., 18.99, -8., 'Homes', 'Fast'),
('FY24', 126.16748411, 1., 18.95, -0., 'Homes', 'Fast'),
('FY25', 127.786528 , 1., 18.96, 0., 'Homes', 'Fast'),
('FY20', 294.366836 , nan, 22.19, nan, 'Businesses', 'Fast'),
('FY21', 249.14807381, -15., 23.89, 8., 'Businesses', 'Fast'),
('FY22', 245.99078563, -2., 23.74, -1., 'Businesses', 'Fast'),
('FY23', 245.70060721, 0., 23.42, -1., 'Businesses', 'Fast'),
('FY24', 247.32146083, 1., 23.37, -0., 'Businesses', 'Fast'),
('FY25', 250.30828813, 1., 23.33, -0., 'Businesses', 'Fast'),
('FY20', 184.631684 , nan, 15.47, nan, 'Total', 'Medium'),
('FY21', 274.25718084, 49., 15.53, 0., 'Total', 'Medium'),
('FY22', 333.23835913, 21., 15.33, -1., 'Total', 'Medium'),
('FY23', 357.33167549, 7., 15.52, 1., 'Total', 'Medium'),
('FY24', 367.84796426, 3., 15.53, 0., 'Total', 'Medium'),
('FY25', 370.1664439 , 1., 15.53, 0., 'Total', 'Medium'),
('FY20', 46.522416 , nan, 17.89, nan, 'Homes', 'Medium'),
('FY21', 97.63428522, 112., 18.72, 5., 'Homes', 'Medium'),
('FY22', 141.25547499, 46., 17.86, -5., 'Homes', 'Medium'),
('FY23', 157.06766598, 11., 18.33, 3., 'Homes', 'Medium'),
('FY24', 163.02337094, 4., 18.29, -0., 'Homes', 'Medium'),
('FY25', 165.98360465, 1., 18.28, -0., 'Homes', 'Medium'),
('FY20', 138.109268 , nan, 14.66, nan, 'Businesses', 'Medium'),
('FY21', 177.62289562, 28., 13.77, -6., 'Businesses', 'Medium'),
('FY22', 191.98288414, 8., 13.46, -2., 'Businesses', 'Medium'),
('FY23', 200.26400951, 4., 13.31, -1., 'Businesses', 'Medium'),
('FY24', 203.82459332, 2., 13.31, 0., 'Businesses', 'Medium'),
('FY25', 205.18283926, 1., 13.31, 0., 'Businesses', 'Medium')],
dtype=[('FY', 'O'), ('ADV', '<f8'), ('YoY_ADV', '<f8'), ('Yield', '<f8'), ('YoY_Yld', '<f8'), ('Cut', 'O'), ('Product', 'O')])
我很難找到將資料to_records()幀再次轉換回資料幀的示例。如何將此資料轉換為資料框？
uj5u.com熱心網友回復：
確保rec和nan是從以下匯入的numpy：
from numpy import rec, nan
a = rec.array([('FY20', 361.410592, nan, 21.97, nan, 'Total', 'Fast'), ('FY21', 359.26952604, -1., 22.99, 5., 'Total', 'Fast'), ('FY22', 362.4560529, 1., 22.77, -1., 'Total', 'Fast'), ('FY23', 371.53543252, 2., 21.92, -4., 'Total', 'Fast'), ('FY24', 374.48894494, 1., 21.88, -0., 'Total', 'Fast'), ('FY25', 377.09481613, 1., 21.85, -0., 'Total', 'Fast'), ('FY20', 67.043756, nan, 21., nan, 'Homes', 'Fast'), ('FY21', 110.12145222, 63., 20.95, -0., 'Homes', 'Fast'), ('FY22', 117.46526727, 7., 20.73, -1., 'Homes', 'Fast'), ('FY23', 125.83482531, 7., 18.99, -8., 'Homes', 'Fast'), ('FY24', 126.16748411, 1., 18.95, -0., 'Homes', 'Fast'), ('FY25', 127.786528, 1., 18.96, 0., 'Homes', 'Fast'), ('FY20', 294.366836, nan, 22.19, nan, 'Businesses', 'Fast'), ('FY21', 249.14807381, -15., 23.89, 8., 'Businesses', 'Fast'), ('FY22', 245.99078563, -2., 23.74, -1., 'Businesses', 'Fast'), ('FY23', 245.70060721, 0., 23.42, -1., 'Businesses', 'Fast'), ('FY24', 247.32146083, 1., 23.37, -0., 'Businesses', 'Fast'), ('FY25', 250.30828813, 1., 23.33, -0., 'Businesses', 'Fast'), ('FY20', 184.631684, nan, 15.47, nan, 'Total', 'Medium'), ('FY21', 274.25718084, 49., 15.53, 0., 'Total', 'Medium'), ('FY22', 333.23835913, 21., 15.33, -1., 'Total', 'Medium'), ('FY23', 357.33167549, 7., 15.52, 1., 'Total', 'Medium'), ('FY24', 367.84796426, 3., 15.53, 0., 'Total', 'Medium'), ('FY25', 370.1664439, 1., 15.53, 0., 'Total', 'Medium'), ('FY20', 46.522416, nan, 17.89, nan, 'Homes', 'Medium'), ('FY21', 97.63428522, 112., 18.72, 5., 'Homes', 'Medium'), ('FY22', 141.25547499, 46., 17.86, -5., 'Homes', 'Medium'), ('FY23', 157.06766598, 11., 18.33, 3., 'Homes', 'Medium'), ('FY24', 163.02337094, 4., 18.29, -0., 'Homes', 'Medium'), ('FY25', 165.98360465, 1., 18.28, -0., 'Homes', 'Medium'), ('FY20', 138.109268, nan, 14.66, nan, 'Businesses', 'Medium'), ('FY21', 177.62289562, 28., 13.77, -6., 'Businesses', 'Medium'), ('FY22', 191.98288414, 8., 13.46, -2., 'Businesses', 'Medium'), ('FY23', 200.26400951, 4., 13.31, -1., 'Businesses', 'Medium'), ('FY24', 203.82459332, 2., 13.31, 0., 'Businesses', 'Medium'), ('FY25', 205.18283926, 1., 13.31, 0., 'Businesses', 'Medium')], dtype=[('FY', 'O'), ('ADV', '<f8'), ('YoY_ADV', '<f8'), ('Yield', '<f8'), ('YoY_Yld', '<f8'), ('Cut', 'O'), ('Product', 'O')])
然后將它傳遞給pd.DataFrame建構式：
import pandas as pd
df = pd.DataFrame(a)
# FY ADV YoY_ADV Yield YoY_Yld Cut Product
# 0 FY20 361.410592 NaN 21.97 NaN Total Fast
# 1 FY21 359.269526 -1.0 22.99 5.0 Total Fast
# 2 FY22 362.456053 1.0 22.77 -1.0 Total Fast
# 3 FY23 371.535433 2.0 21.92 -4.0 Total Fast
# 4 FY24 374.488945 1.0 21.88 -0.0 Total Fast
# 5 FY25 377.094816 1.0 21.85 -0.0 Total Fast
# 6 FY20 67.043756 NaN 21.00 NaN Homes Fast
# 7 FY21 110.121452 63.0 20.95 -0.0 Homes Fast
# 8 FY22 117.465267 7.0 20.73 -1.0 Homes Fast
# 9 FY23 125.834825 7.0 18.99 -8.0 Homes Fast
# 10 FY24 126.167484 1.0 18.95 -0.0 Homes Fast
# 11 FY25 127.786528 1.0 18.96 0.0 Homes Fast
# 12 FY20 294.366836 NaN 22.19 NaN Businesses Fast
# 13 FY21 249.148074 -15.0 23.89 8.0 Businesses Fast
# 14 FY22 245.990786 -2.0 23.74 -1.0 Businesses Fast
# 15 FY23 245.700607 0.0 23.42 -1.0 Businesses Fast
# 16 FY24 247.321461 1.0 23.37 -0.0 Businesses Fast
# 17 FY25 250.308288 1.0 23.33 -0.0 Businesses Fast
# 18 FY20 184.631684 NaN 15.47 NaN Total Medium
# 19 FY21 274.257181 49.0 15.53 0.0 Total Medium
# 20 FY22 333.238359 21.0 15.33 -1.0 Total Medium
# 21 FY23 357.331675 7.0 15.52 1.0 Total Medium
# 22 FY24 367.847964 3.0 15.53 0.0 Total Medium
# 23 FY25 370.166444 1.0 15.53 0.0 Total Medium
# 24 FY20 46.522416 NaN 17.89 NaN Homes Medium
# 25 FY21 97.634285 112.0 18.72 5.0 Homes Medium
# 26 FY22 141.255475 46.0 17.86 -5.0 Homes Medium
# 27 FY23 157.067666 11.0 18.33 3.0 Homes Medium
# 28 FY24 163.023371 4.0 18.29 -0.0 Homes Medium
# 29 FY25 165.983605 1.0 18.28 -0.0 Homes Medium
# 30 FY20 138.109268 NaN 14.66 NaN Businesses Medium
# 31 FY21 177.622896 28.0 13.77 -6.0 Businesses Medium
# 32 FY22 191.982884 8.0 13.46 -2.0 Businesses Medium
# 33 FY23 200.264010 4.0 13.31 -1.0 Businesses Medium
# 34 FY24 203.824593 2.0 13.31 0.0 Businesses Medium
# 35 FY25 205.182839 1.0 13.31 0.0 Businesses Medium
轉載請註明出處，本文鏈接：https://www.uj5u.com/net/376309.html