Convertir Excel a DataFrame de Pandas

Usando Aspose.Cells para Python via .NET API, puedes convertir Excel, TSV, CSV, Json y muchos formatos diferentes 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 import Workbook, Worksheet, Cells

# 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 = []
header_row = None
for row in cells.rows.__iter__():
    if row is None:
        continue
    header_row = row
    for cell in row.__iter__():
        columnDatas.append(cell.value)
    break

result = pd.DataFrame(columns=columnDatas, dtype=object)

row_index = 0
for row in cells.rows.__iter__():
    if row is None:
        continue
    if row == header_row:
        continue

    row_values = []
    for cell in row.__iter__():
        row_values.append(cell.value)

    # print(row_values)
    result.loc[row_index] = row_values
    row_index += 1

print(result)