Convertir Excel en DataFrame Pandas
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En utilisant l’API Aspose.Cells pour Python via .NET, vous pouvez convertir Excel, TSV, CSV, JSON et de nombreux autres formats en DataFrame Pandas.
Convertir Excel en DataFrame Pandas via des données json
Voici un exemple de code pour démontrer comment exporter des données excel vers un DataFrame Pandas via des données json en utilisant Aspose.Cells pour Python via .NET :
- Créer un classeur et ajouter des valeurs.
- Exporter les données excel en chaîne JSON.
- Utiliser la bibliothèque pandas pour lire les données JSON.
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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 le DataFrame Pandas en Excel directement
Voici un exemple de code pour démontrer comment exporter directement les données excel vers un DataFrame Pandas en utilisant Aspose.Cells pour Python via .NET :
- Créer un classeur et ajouter des valeurs.
- Parcourir les données excel et exporter les données vers le DataFrame Pandas en utilisant Aspose.Cells pour Python via .NET.
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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) |