Convertire Excel in DataFrame Pandas.
Contents
[
Hide
]
Utilizzando Aspose.Cells per Python via .NET API, è possibile convertire Excel, TSV, CSV, Json e molti formati diversi in DataFrame pandas.
Convertire Excel in DataFrame Pandas tramite dati json.
Ecco un esempio di snippet di codice per dimostrare come esportare i dati dell’excel in un DataFrame pandas tramite dati json utilizzando Aspose.Cells per Python via .NET:
- Creare un documento di lavoro e aggiungere alcuni valori.
- Esportare i dati dell’excel in una stringa JSON.
- Utilizzare la libreria pandas per leggere i dati JSON.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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) |
Convertire direttamente il DataFrame di Pandas in Excel
Ecco un esempio di snippet di codice per dimostrare come esportare i dati dell’excel direttamente in un DataFrame pandas utilizzando Aspose.Cells per Python via .NET:
- Creare un documento di lavoro e aggiungere alcuni valori.
- Attraversare i dati di Excel ed esportare i dati nel DataFrame di Pandas usando Aspose.Cells per Python via .NET.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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) |