是否可以在 Dash 中上传 csv 文件并将其存储为 pandas DataFrame?
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【中文标题】是否可以在 Dash 中上传 csv 文件并将其存储为 pandas DataFrame?【英文标题】:Is it possible to upload a csv file in Dash and also store it as a pandas DataFrame? 【发布时间】:2021-09-11 19:47:09 【问题描述】:我正在使用 Python 在 Dash 中开发仪表板,并且在其中一个核心组件中我正在尝试上传 csv 文件并以数据表格式显示(见下文)。效果很好(见图),我按照这个例子:https://dash.plotly.com/dash-core-components/upload
但是,我还想在代码后面使用该表作为 pandas DataFrame。由于我在运行仪表板代码后上传了 csv 文件,因此我找不到将 csv 内容作为 DataFrame 返回的方法。有什么方法可以做到这一点?我的代码如下。
Dash app output
提前谢谢你!
###############################################################################
# Upload files
# https://dash.plotly.com/dash-core-components/upload
###############################################################################
def parse_contents(contents, filename, date):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
try:
if 'csv' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8')))
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded))
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
trade_upload = pd.DataFrame(df)
return dbc.Table.from_dataframe(trade_upload)
@app.callback(Output('output-data-upload', 'children'),
[Input('upload-data', 'contents')],
[State('upload-data', 'filename'),
State('upload-data', 'last_modified')])
def update_output(list_of_contents, list_of_names, list_of_dates):
if list_of_contents is not None:
children = [
parse_contents(c, n, d) for c, n, d in
zip(list_of_contents, list_of_names, list_of_dates)]
return children
if __name__ == '__main__':
app.run_server(port=8051, debug=False)
【问题讨论】:
【参考方案1】:定义parse_contents
函数时,可以简单的return df
:
def parse_contents(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
try:
if 'csv' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8')))
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded))
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
return df
然后,您可以在以下回调中调用parse_contents
并生成熊猫数据框:
@app.callback(
Output('table-container', 'data'),
[Input('file_upload', 'contents')],
State('file_upload', 'filename'))
def filter_df(content, name):
if content is not None:
# Return all the rows on initial load/no country selected.
df = parse_contents(content, name)
dff = df.to_json()
dff_pandas = pd.Dataframe(dff)
else:
df = parse_contents(content, name)
dff = df.to_json()
dff_pandas = pd.Dataframe(dff)
dff_pandas_filtered = dff_pandas.query('column_A == 012345')
【讨论】:
这个解决方案似乎不起作用。它返回以下错误:Property "data" was used with component ID: "table-container" in one of the Output items of a callback. This ID is assigned to a dash_html_components.Div component in the layout, which does not support this property. This ID was used in the callback(s) for Output(s): table-container.data
【参考方案2】:
您可以将其保留为全局变量。下面是单个文件上传的代码。
1.布局
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select Files')
]),
style=
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
,
# Allow multiple files to be uploaded
multiple=False
),
html.Div(id='output-data-upload'),
])
2.功能
def parse_contents(contents, filename, date):
content_type, content_string = contents.split(',')
global df#define data frame as global
decoded = base64.b64decode(content_string)
try:
if 'csv' in filename:
# Assume that the user uploaded a CSV file
df = pd.read_csv(
io.StringIO(decoded.decode('utf-8')))
elif 'xls' in filename:
# Assume that the user uploaded an excel file
df = pd.read_excel(io.BytesIO(decoded))
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
return html.Div([
html.H5(filename),
html.H6(datetime.datetime.fromtimestamp(date)),
dash_table.DataTable(
data=df.to_dict('records'),
columns=['name': i, 'id': i for i in df.columns]
),
html.Hr(), # horizontal line
# For debugging, display the raw contents provided by the web browser
html.Div('Raw Content'),
html.Pre(contents[0:200] + '...', style=
'whiteSpace': 'pre-wrap',
'wordBreak': 'break-all'
)
])
3.回调
@app.callback(Output('output-data-upload', 'children'),
Input('upload-data', 'contents'),
State('upload-data', 'filename'),
State('upload-data', 'last_modified'))
def update_output(content, filename, date):
children=parse_contents(content, filename, date)
print(type(df))#this will show data type as a pandas dataframe
print(df)
return children
【讨论】:
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