Convertir Excel a DataFrame de Pandas

Convertir Excel a DataFrame de Pandas a través de datos json

Aquí tienes un ejemplo de código para demostrar cómo exportar datos de Excel a un DataFrame de Pandas a través de datos json utilizando Aspose.Cells para Python via .NET:

  1. Crea un libro de trabajo y agrega algunos valores.
  2. Exportar datos de excel a cadena JSON.
  3. Utiliza la librería pandas para leer datos JSON.
import pandas as pd
from aspose.cells.utility import JsonUtility, JsonLayoutOptions
from aspose.cells import Workbook, Worksheet, Cells, JsonSaveOptions
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Get the first worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
# Add some values
cells.get("A1").value = "Name"
cells.get("B1").value = "Age"
cells.get("C1").value = "City"
cells.get("A2").value = "Alice"
cells.get("B2").value = 25
cells.get("C2").value = "New York"
cells.get("A3").value = "Bob"
cells.get("B3").value = 30
cells.get("C3").value = "San Francisco"
cells.get("A4").value = "Charlie"
cells.get("B4").value = 35
cells.get("C4").value = "Los Angeles"
jsonSaveOptions = JsonSaveOptions()
# Save data to json string
json = JsonUtility.export_range_to_json(cells.max_display_range, jsonSaveOptions);
print(json)
# Read json string using pandas
dfData = pd.read_json(json)
print(dfData)

Convertir DataFrame de Pandas a Excel directamente

Aquí tienes un ejemplo de código para demostrar cómo exportar datos de Excel a un DataFrame de Pandas directamente utilizando Aspose.Cells para Python via .NET:

  1. Crea un libro de trabajo y agrega algunos valores.
  2. Recorrer los datos de Excel y exportar datos a DataFrame de Pandas utilizando Aspose.Cells para Python via .NET.
import pandas as pd
from aspose.cells.utility import JsonUtility, JsonLayoutOptions
from aspose.cells import Workbook, Worksheet, Cells, JsonSaveOptions
# Create a new Aspose.Cells Workbook
workbook = Workbook()
# Get the first worksheet
worksheet = workbook.worksheets[0]
# Get the cells
cells = worksheet.cells
# Add some values
cells.get("A1").value = "Name"
cells.get("B1").value = "Age"
cells.get("C1").value = "City"
cells.get("A2").value = "Alice"
cells.get("B2").value = 25
cells.get("C2").value = "New York"
cells.get("A3").value = "Bob"
cells.get("B3").value = 30
cells.get("C3").value = "San Francisco"
cells.get("A4").value = "Charlie"
cells.get("B4").value = 35
cells.get("C4").value = "Los Angeles"
rowCount = cells.max_data_row
columnCount = cells.max_data_column
columnDatas=[]
for c in range(columnCount + 1):
currCell = cells.get_cell(0, c)
columnDatas.append(currCell.value)
result = pd.DataFrame(columns=columnDatas, dtype=object)
for i in range(1, rowCount + 1):
rowarray = []
for j in range(columnCount + 1):
currCell = cells.get_cell(i, j)
rowarray.append(currCell.value)
print(rowarray)
result.loc[i - 1] = rowarray
print(result)