Ste*_*ara 3 python pandas plotly plotly-dash
我试图在我的仪表卡上添加千位分隔符,但我所有的努力都是徒劳的。发现这个解决方案更准确,但它给了我一个错误
类型错误:传递给系列的格式字符串不受支持。格式
@app.callback(
[Output('sls', 'children'),
Output('wngs', 'children'),
Output('rvne', 'children')],
Input('year', 'value')
)
def card_update(select_year):
dff=df_good.copy()
df_formattedd=dff.groupby(['year'], as_index=False)[['Net Sale', 'Winnings','Revenue']].sum()
df_formattedd[['Net Sale','Winnings','Revenue']]=df_formattedd[['Net Sale','Winnings','Revenue']].apply(lambda x:round(x,2))
df_formattedd[['Net Sale','Winnings','Revenue']]= df_formattedd[['Net Sale','Winnings','Revenue']].apply(lambda x: f'{x:,}')
sales=df_formattedd[df_formattedd['year']==select_year]['Net Sale']
winnings=df_formattedd[df_formattedd['year']==select_year]['Winnings']
revenue=df_formattedd[df_formattedd['year']==select_year]['Revenue']
return sales, winnings, revenue
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Bas*_*den 10
重现您的问题的简短抽象示例代码:
import pandas as pd
df = pd.DataFrame(
{
"A": [1000000.111, 1000000.222, 1000000.333],
"B": [2000000.111, 2000000.222, 2000000.333],
"C": [3000000.111, 3000000.222, 3000000.333],
}
)
df[["A", "B", "C"]] = df[["A", "B", "C"]].apply(lambda x: round(x, 2))
df[["A", "B", "C"]] = df[["A", "B", "C"]].apply(lambda x: f'{x:,}')
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给出:
类型错误:传递给系列的格式字符串不受支持。格式
问题出在您尝试格式化数字的最后一行。
问题是xlambda 函数引用的是 Pandas Series 而不是数字。系列不支持您正在使用的格式化字符串类型:
',' 选项表示使用逗号作为千位分隔符。
https://docs.python.org/3/library/string.html
相反,你可以这样做:
import pandas as pd
df = pd.DataFrame(
{
"A": [1000000.111, 1000000.222, 1000000.333],
"B": [2000000.111, 2000000.222, 2000000.333],
"C": [3000000.111, 3000000.222, 3000000.333],
}
)
df[["A", "B", "C"]] = df[["A", "B", "C"]].apply(lambda x: round(x, 2))
df[["A", "B", "C"]] = df[["A", "B", "C"]].apply(
lambda series: series.apply(lambda value: f"{value:,}")
)
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因此,这里嵌套背后的想法apply是:对于 DataFrame 中的每一列,df[["A", "B", "C"]]获取每一行值并将字符串格式化程序应用于它。行值只是浮点数,因此字符串格式化程序能够处理它。
结果
>>> print(df)
A B C
0 1,000,000.11 2,000,000.11 3,000,000.11
1 1,000,000.22 2,000,000.22 3,000,000.22
2 1,000,000.33 2,000,000.33 3,000,000.33
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或者,您可以使用以下方式设置格式pd.options.display.float_format:
pd.options.display.float_format = "{:,}".format
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请记住,这不仅仅适用于df[["A", "B", "C"]].