NumPy yı Excel e dönüştürün

NumPy’ya Giriş

NumPy (Sayısal Python), Python’un açık kaynaklı sayısal hesaplama uzantısıdır. Bu araç, büyük matrisleri depolamak ve işlemek için kullanılabilir ve Python’un iç içe liste yapısından (matrisleri temsil etmek için de kullanılabilir) çok daha verimlidir. Büyük sayıda boyutlu dizileri ve matris işlemlerini destekler ve ayrıca dizi işlemleri için geniş bir matematiksel işlev kütüphanesi sağlar.

NumPy’nın temel işlevleri:

  1. Ndarray, hızlı, esnek ve yer tasarrufu sağlayan çok boyutlu dizi nesnesidir.
  2. Matris çarpımı, transpozisyon, ters çevirme vb. içeren lineer cebir işlemleri.
  3. Fourier dönüşümü, bir dizide hızlı Fourier dönüşümü yapma.
  4. Kayan noktalı dizilerin hızlı işlemi.
  5. Python içine C dil kodunu entegre ederek daha hızlı çalışmasını sağlama.

Aspose.Cells for Python via .NET API’sını kullanarak NumPy ndarray’ını Excel, OpenOffice, Pdf, Json ve çok farklı formatlara dönüştürebilirsiniz.

NumPy’nı Excel Çalışma Kitabına Nasıl Dönüştürülür

Aspose.Cells for Python via .NET kullanarak bir NumPy dizisinden veri almayı gösteren bir örnek kod parçacığı:

  1. Örnek bir NumPy dizisi verisi oluşturun.
  2. NumPy dizisini dolaşın ve Aspose.Cells for Python via .NET kullanarak veri alın.
import numpy as np
import pandas as pd
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range, CellsHelper
def put_cell_value(cells, raw_value, row , column):
cell = cells.get(row , column)
dtype = type(raw_value)
match dtype:
case np.bool_ :
value = bool(raw_value)
case np.int_ :
value = int(raw_value)
case np.intc :
value = int(raw_value)
case np.intp :
value = int(raw_value)
case np.int8 :
value = int(raw_value)
case np.int16 :
value = int(raw_value)
case np.int32 :
value = int(raw_value)
case np.int64 :
value = int(raw_value)
case np.uint8 :
value = int(raw_value)
case np.uint16 :
value = int(raw_value)
case np.uint32 :
value = int(raw_value)
case np.uint64 :
value = int(raw_value)
case np.float_:
value = int(raw_value)
case np.float16:
value = float(raw_value)
case np.float32:
value = float(raw_value)
case np.float64:
value = float(raw_value)
case np.single:
value = float(raw_value)
case np.double:
value = float(raw_value)
case np.datetime64 :
ts = pd.to_datetime(str(raw_value))
value = ts.strftime('%Y.%m.%d')
case _:
value = raw_value
cell.put_value(value)
pass
def import_table_data_into_cells(cells,table_data,row_index,column_index,is_vertical):
table_row_index = row_index
table_column_index = column_index
row_count = len( table_data)
column_count = 0
for table_row in table_data:
for table_cell in table_row:
column_count =len( table_row)
put_cell_value(cells,table_cell,table_row_index,table_column_index)
if is_vertical :
table_row_index = table_row_index + 1
else:
table_column_index = table_column_index + 1
if is_vertical :
table_row_index = row_index
table_column_index = table_column_index + 1
else:
table_column_index = column_index
table_row_index = table_row_index + 1
if is_vertical :
end_row_index = row_index + row_count - 1
end_column_index = table_column_index - 1
else:
end_row_index = table_row_index - 1
end_column_index = column_index + column_count - 1
return (row_index,column_index,end_row_index,end_column_index)
excel_data = np.array([[['City', 'Region', 'Store'], ['Chicago', 'Central', 3055], ['New York', 'East', 3036], ['Detroit', 'Central', 3074]],
[['City2', 'Region2', 'Store3'], ['Seattle', 'West', 3000], ['philadelph', 'East', 3082], ['Detroit', 'Central', 3074]], [['City3', 'Region3', 'Store3'], ['Seattle', 'West', 3166], ['New York', 'East', 3090], ['Chicago', 'Central', 3055]]] )
# Create a new Aspose.Cells Workbook
workbook = Workbook()
begin_row_index = 0
begin_column_index = 0
is_vertical = False
sheet_index = 1
for table_data in excel_data:
curr_sheet = workbook.worksheets.add("Sheet_data_" + str(sheet_index))
curr_cells = curr_sheet.cells
import_table_data_into_cells(curr_cells , table_data , begin_row_index,begin_column_index,is_vertical)
sheet_index += 1
workbook.save("out.xlsx")
view raw Numpy-import-ndarray-to-excel.py hosted with ❤ by GitHub

Çıktı sonucu:

NumPy ndarray’yi Çalışma Sayfasına Nasıl Dönüştürülür

Aspose.Cells for Python via .NET kullanarak bir NumPy dizisinden veri almayı gösteren bir örnek kod parçacığı:

  1. Örnek bir NumPy dizisi verisi oluşturun.
  2. NumPy dizisini dolaşın ve Aspose.Cells for Python via .NET kullanarak veri alın.
import numpy as np
import pandas as pd
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range, CellsHelper
def put_cell_value(cells, raw_value, row , column):
cell = cells.get(row , column)
dtype = type(raw_value)
match dtype:
case np.bool_ :
value = bool(raw_value)
case np.int_ :
value = int(raw_value)
case np.intc :
value = int(raw_value)
case np.intp :
value = int(raw_value)
case np.int8 :
value = int(raw_value)
case np.int16 :
value = int(raw_value)
case np.int32 :
value = int(raw_value)
case np.int64 :
value = int(raw_value)
case np.uint8 :
value = int(raw_value)
case np.uint16 :
value = int(raw_value)
case np.uint32 :
value = int(raw_value)
case np.uint64 :
value = int(raw_value)
case np.float_:
value = int(raw_value)
case np.float16:
value = float(raw_value)
case np.float32:
value = float(raw_value)
case np.float64:
value = float(raw_value)
case np.single:
value = float(raw_value)
case np.double:
value = float(raw_value)
case np.datetime64 :
ts = pd.to_datetime(str(raw_value))
value = ts.strftime('%Y.%m.%d')
case _:
value = raw_value
cell.put_value(value)
pass
def import_table_data_into_cells(cells,table_data,row_index,column_index,is_vertical):
table_row_index = row_index
table_column_index = column_index
row_count = len( table_data)
column_count = 0
for table_row in table_data:
for table_cell in table_row:
column_count =len( table_row)
put_cell_value(cells,table_cell,table_row_index,table_column_index)
if is_vertical :
table_row_index = table_row_index + 1
else:
table_column_index = table_column_index + 1
if is_vertical :
table_row_index = row_index
table_column_index = table_column_index + 1
else:
table_column_index = column_index
table_row_index = table_row_index + 1
if is_vertical :
end_row_index = row_index + row_count - 1
end_column_index = table_column_index - 1
else:
end_row_index = table_row_index - 1
end_column_index = column_index + column_count - 1
return (row_index,column_index,end_row_index,end_column_index)
# Create a sample NumPy array
data = np.array([['City', 'Region', 'Store'], ['Chicago', 'Central', 3055], ['New York', 'East', 3036], ['Detroit', 'Central', 3074]])
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Access the first (default) worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
begin_row_index = 0
begin_column_index = 0
is_vertical = False
import_table_data_into_cells(cells , data , begin_row_index,begin_column_index,is_vertical)
workbook.save("out.xlsx")
view raw Numpy-import-ndarray-to-worksheet.py hosted with ❤ by GitHub

Çıktı sonucu:

NumPy ndarray’yi ListObject’e Nasıl Dönüştürülür

Aspose.Cells for Python via .NET kullanarak bir NumPy dizisinden veri almayı gösteren bir örnek kod parçacığı:

  1. Örnek bir NumPy dizisi verisi oluşturun.
  2. NumPy dizisini dolaşın ve Aspose.Cells for Python via .NET kullanarak veri alın. Örnek veri kullanarak ListObject nesnesi oluşturun.
import numpy as np
import pandas as pd
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range, CellsHelper
def put_cell_value(cells, raw_value, row , column):
cell = cells.get(row , column)
dtype = type(raw_value)
match dtype:
case np.bool_ :
value = bool(raw_value)
case np.int_ :
value = int(raw_value)
case np.intc :
value = int(raw_value)
case np.intp :
value = int(raw_value)
case np.int8 :
value = int(raw_value)
case np.int16 :
value = int(raw_value)
case np.int32 :
value = int(raw_value)
case np.int64 :
value = int(raw_value)
case np.uint8 :
value = int(raw_value)
case np.uint16 :
value = int(raw_value)
case np.uint32 :
value = int(raw_value)
case np.uint64 :
value = int(raw_value)
case np.float_:
value = int(raw_value)
case np.float16:
value = float(raw_value)
case np.float32:
value = float(raw_value)
case np.float64:
value = float(raw_value)
case np.single:
value = float(raw_value)
case np.double:
value = float(raw_value)
case np.datetime64 :
ts = pd.to_datetime(str(raw_value))
value = ts.strftime('%Y.%m.%d')
case _:
value = raw_value
cell.put_value(value)
pass
def import_table_data_into_cells(cells,table_data,row_index,column_index,is_vertical):
table_row_index = row_index
table_column_index = column_index
row_count = len( table_data)
column_count = 0
for table_row in table_data:
for table_cell in table_row:
column_count =len( table_row)
put_cell_value(cells,table_cell,table_row_index,table_column_index)
if is_vertical :
table_row_index = table_row_index + 1
else:
table_column_index = table_column_index + 1
if is_vertical :
table_row_index = row_index
table_column_index = table_column_index + 1
else:
table_column_index = column_index
table_row_index = table_row_index + 1
if is_vertical :
end_row_index = row_index + row_count - 1
end_column_index = table_column_index - 1
else:
end_row_index = table_row_index - 1
end_column_index = column_index + column_count - 1
return (row_index,column_index,end_row_index,end_column_index)
# Create a sample NumPy array
data = np.array([['City', 'Region', 'Store'], ['Chicago', 'Central', 3055], ['New York', 'East', 3036], ['Detroit', 'Central', 3074]])
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Access the first (default) worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
begin_row_index = 0
begin_column_index = 0
is_vertical = False
# ndarray to listobject
(begin_row_index,begin_column_index,end_row_index,end_column_index) = import_table_data_into_cells(cells , data , begin_row_index,begin_column_index,is_vertical)
start_cell = CellsHelper.cell_index_to_name(begin_row_index, begin_column_index)
end_cell = CellsHelper.cell_index_to_name(end_row_index, end_column_index)
index = worksheet.list_objects.add(start_cell, end_cell,True)
workbook.save("out.xlsx")
view raw Numpy-import-ndarray-to-listobject.py hosted with ❤ by GitHub

Çıktı sonucu:

NumPy ndarray’yi Aralık’a Nasıl Dönüştürülür

Aspose.Cells for Python via .NET kullanarak bir NumPy dizisinden veri almayı gösteren bir örnek kod parçacığı:

  1. Örnek bir NumPy dizisi verisi oluşturun.
  2. NumPy dizisini dolaşın ve Aspose.Cells for Python via .NET kullanarak veri alın. Örnek veri kullanarak Range nesnesi oluşturun.
import numpy as np
import pandas as pd
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range, CellsHelper
def put_cell_value(cells, raw_value, row , column):
cell = cells.get(row , column)
dtype = type(raw_value)
match dtype:
case np.bool_ :
value = bool(raw_value)
case np.int_ :
value = int(raw_value)
case np.intc :
value = int(raw_value)
case np.intp :
value = int(raw_value)
case np.int8 :
value = int(raw_value)
case np.int16 :
value = int(raw_value)
case np.int32 :
value = int(raw_value)
case np.int64 :
value = int(raw_value)
case np.uint8 :
value = int(raw_value)
case np.uint16 :
value = int(raw_value)
case np.uint32 :
value = int(raw_value)
case np.uint64 :
value = int(raw_value)
case np.float_:
value = int(raw_value)
case np.float16:
value = float(raw_value)
case np.float32:
value = float(raw_value)
case np.float64:
value = float(raw_value)
case np.single:
value = float(raw_value)
case np.double:
value = float(raw_value)
case np.datetime64 :
ts = pd.to_datetime(str(raw_value))
value = ts.strftime('%Y.%m.%d')
case _:
value = raw_value
cell.put_value(value)
pass
def import_table_data_into_cells(cells,table_data,row_index,column_index,is_vertical):
table_row_index = row_index
table_column_index = column_index
row_count = len( table_data)
column_count = 0
for table_row in table_data:
for table_cell in table_row:
column_count =len( table_row)
put_cell_value(cells,table_cell,table_row_index,table_column_index)
if is_vertical :
table_row_index = table_row_index + 1
else:
table_column_index = table_column_index + 1
if is_vertical :
table_row_index = row_index
table_column_index = table_column_index + 1
else:
table_column_index = column_index
table_row_index = table_row_index + 1
if is_vertical :
end_row_index = row_index + row_count - 1
end_column_index = table_column_index - 1
else:
end_row_index = table_row_index - 1
end_column_index = column_index + column_count - 1
return (row_index,column_index,end_row_index,end_column_index)
# Create a sample NumPy array
data = np.array([['City', 'Region', 'Store'], ['Chicago', 'Central', 3055], ['New York', 'East', 3036], ['Detroit', 'Central', 3074]])
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Access the first (default) worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
begin_row_index = 0
begin_column_index = 0
is_vertical = False
# ndarray to range
(begin_row_index,begin_column_index,end_row_index,end_column_index) = import_table_data_into_cells(cells , data , begin_row_index,begin_column_index,is_vertical)
start_cell = CellsHelper.cell_index_to_name(begin_row_index, begin_column_index)
end_cell = CellsHelper.cell_index_to_name(end_row_index, end_column_index)
range_obj = cells.create_range(start_cell, end_cell)
print("row count: " + str(range_obj.row_count))
print("column count: " + str(range_obj.column_count))
workbook.save("out.xlsx")
view raw Numpy-import-ndarray-to-range.py hosted with ❤ by GitHub

Çıktı sonucu:

row count: 4
column count: 3

NumPy ndarray’yi İsim’e Nasıl Dönüştürülür

Aspose.Cells for Python via .NET kullanarak bir NumPy dizisinden veri almayı gösteren bir örnek kod parçacığı:

  1. Örnek bir NumPy dizisi verisi oluşturun.
  2. NumPy dizisini dolaşın ve Aspose.Cells for Python via .NET kullanarak veri alın. Örnek veri kullanarak Name nesnesi oluşturun.
import numpy as np
import pandas as pd
import aspose.cells
from aspose.cells import Workbook, Worksheet, Range, CellsHelper
def put_cell_value(cells, raw_value, row , column):
cell = cells.get(row , column)
dtype = type(raw_value)
match dtype:
case np.bool_ :
value = bool(raw_value)
case np.int_ :
value = int(raw_value)
case np.intc :
value = int(raw_value)
case np.intp :
value = int(raw_value)
case np.int8 :
value = int(raw_value)
case np.int16 :
value = int(raw_value)
case np.int32 :
value = int(raw_value)
case np.int64 :
value = int(raw_value)
case np.uint8 :
value = int(raw_value)
case np.uint16 :
value = int(raw_value)
case np.uint32 :
value = int(raw_value)
case np.uint64 :
value = int(raw_value)
case np.float_:
value = int(raw_value)
case np.float16:
value = float(raw_value)
case np.float32:
value = float(raw_value)
case np.float64:
value = float(raw_value)
case np.single:
value = float(raw_value)
case np.double:
value = float(raw_value)
case np.datetime64 :
ts = pd.to_datetime(str(raw_value))
value = ts.strftime('%Y.%m.%d')
case _:
value = raw_value
cell.put_value(value)
pass
def import_table_data_into_cells(cells,table_data,row_index,column_index,is_vertical):
table_row_index = row_index
table_column_index = column_index
row_count = len( table_data)
column_count = 0
for table_row in table_data:
for table_cell in table_row:
column_count =len( table_row)
put_cell_value(cells,table_cell,table_row_index,table_column_index)
if is_vertical :
table_row_index = table_row_index + 1
else:
table_column_index = table_column_index + 1
if is_vertical :
table_row_index = row_index
table_column_index = table_column_index + 1
else:
table_column_index = column_index
table_row_index = table_row_index + 1
if is_vertical :
end_row_index = row_index + row_count - 1
end_column_index = table_column_index - 1
else:
end_row_index = table_row_index - 1
end_column_index = column_index + column_count - 1
return (row_index,column_index,end_row_index,end_column_index)
# Create a sample NumPy array
data = np.array([['City', 'Region', 'Store'], ['Chicago', 'Central', 3055], ['New York', 'East', 3036], ['Detroit', 'Central', 3074]])
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Access the first (default) worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
begin_row_index = 0
begin_column_index = 0
is_vertical = False
# ndarray to Name
(begin_row_index,begin_column_index,end_row_index,end_column_index) = import_table_data_into_cells(cells , data , begin_row_index,begin_column_index,is_vertical)
start_cell = CellsHelper.cell_index_to_name(begin_row_index, begin_column_index)
end_cell = CellsHelper.cell_index_to_name(end_row_index, end_column_index)
name_text = "Name_test"
name_refers_to = "=" + worksheet.name + "!$" + start_cell + ":$" + end_cell
name_index = worksheet.workbook.worksheets.names.add(name_text);
name = worksheet.workbook.worksheets.names[name_index]
name.refers_to = name_refers_to
workbook.save("out.xlsx")
view raw Numpy-import-ndarray-to-name.py hosted with ❤ by GitHub

Çıktı sonucu: