如何根据列值对数据框结果进行排序

Question

如何根据列值对数据框结果进行排序

3

import requests
import pandas as pd

url = "https://coinmarketcap.com/new/"
page = requests.get(url,headers={'User-Agent': 'Mozilla/5.0'}, timeout=1)
pagedata = page.text
usecols = ["Name", "Price", "1h", "24h", "MarketCap", "Volume"]#, "Blockchain"]

df = pd.read_html(pagedata)[0] #Checking table
df[["Name", "Symbol"]] = df["Name"].str.split(r"\d+", expand=True)
df = df.rename(columns={"Fully Diluted Market Cap": "MarketCap"})[usecols]
dfAsString = df.to_string(index=False)

print(dfAsString)

当前代码输出：（已截断）

               Name            Price      1h      24h       MarketCap       Volume
0        DollarPepe         $0.02752  22.64%  336.25%              $3     $456,913
1       Billy Token      $0.00002822  41.69%   75.80%      $1,958,942   $6,999,241
2              JEFF          $0.1946   4.42%  226.18%     $19,458,328  $19,744,583
3            PUG AI   $0.00000001459  10.80%   15.84%      $1,459,428     $239,454
4         FART COIN    $0.0000004281   1.13%   42.13%     $42,806,075      $46,604
[30 rows x 6 columns]

如何根据特定列（24小时）生成排序后的输出？-> 截断

               Name            Price      1h      24h       MarketCap       Volume
0        DollarPepe         $0.02752  22.64%  336.25%              $3     $456,913
2              JEFF          $0.1946   4.42%  226.18%     $19,458,328  $19,744,583
1       Billy Token      $0.00002822  41.69%   75.80%      $1,958,942   $6,999,241
4         FART COIN    $0.0000004281   1.13%   42.13%     $42,806,075      $46,604
3            PUG AI   $0.00000001459  10.80%   15.84%      $1,459,428     $239,454
[30 rows x 6 columns]

- Drew Duazeh

请参见 https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html - Michael Butscher

1个回答

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- Nick · Accepted Answer

我会将您的数据框中的所有数字列转换为数字值；然后您可以轻松地对它们进行排序（您始终可以在显示时添加$和%）。

numcols = df.columns[df.columns != 'Name']
df[numcols] = df[numcols].apply(lambda c:pd.to_numeric(c.str.replace(r'[^\d.]|(?<!\d)\.|\.(?!\d)', '', regex=True)))
df = df.sort_values('24h', ascending=False)

输出（针对您的示例数据）：

          Name         Price     1h     24h  MarketCap    Volume
0   DollarPepe  2.752000e-02  22.64  336.25          3    456913
2         JEFF  1.946000e-01   4.42  226.18   19458328  19744583
1  Billy Token  2.822000e-05  41.69   75.80    1958942   6999241
4    FART COIN  4.281000e-07   1.13   42.13   42806075     46604
3       PUG AI  1.459000e-08  10.80   15.84    1459428    239454

请注意，非数字字符替换比您的示例数据所暗示的[^\d.]更为复杂；这是因为从该页面获取的其他一些价格值中有...（可能是因为它们太小而无法表示）。理想情况下，您需要找出如何将它们作为精确值获取；否则它们只能被近似。

或者，您可以通过将它们转换为浮点数后将系列传递给sort_values来按值排序：

df = df.sort_values('24h', ascending=False, key=lambda v:v.str.replace('%', '').astype(float))

输出：

          Name           Price      1h      24h    MarketCap       Volume
0   DollarPepe        $0.02752  22.64%  336.25%           $3     $456,913
2         JEFF         $0.1946   4.42%  226.18%  $19,458,328  $19,744,583
1  Billy Token     $0.00002822  41.69%   75.80%   $1,958,942   $6,999,241
4    FART COIN   $0.0000004281   1.13%   42.13%  $42,806,075      $46,604
3       PUG AI  $0.00000001459  10.80%   15.84%   $1,459,428     $239,454