<p>您可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">^{<cd1>}</a>+<a href="https://pandas.pydata.org/docs/reference/api/pandas.Series.rank.html" rel="nofollow noreferrer">^{<cd2>}</a>:</p>
<pre><code>df['Points'] = df.groupby('date')['NATR'].rank(method='dense').astype(int)
</code></pre>
<hr/>
<pre><code> date ticker NATR Points
0 2001-02-23 ABC 9.189955 3
1 2001-02-23 ADP 3.300756 1
2 2001-02-23 AGL1 4.443902 2
3 2001-02-24 ALD 7.733580 2
4 2001-02-24 ALL 8.217828 3
5 2001-02-24 ALQ 2.538381 1
6 2001-02-24 ALU 10.394890 4
7 2001-02-25 ALZ 4.970826 3
8 2001-02-25 AMC 4.173612 2
9 2001-02-25 AMP 4.012471 1
10 2001-02-25 ANN 8.280537 4
11 2001-02-26 ANZ 3.775175 1
12 2001-02-26 AOR 7.413381 5
13 2001-02-26 AQP 7.253565 4
14 2001-02-26 ART 4.439084 2
15 2001-02-26 ASX 5.089084 3
16 2001-02-26 AUN 51.088334 6
17 2001-02-27 AUT1 10.018372 2
18 2001-02-27 AWC 5.429162 1
19 2001-02-27 AWE 10.349716 3
</code></pre>