<p>您可以使用<code>dict</code>表示与<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.repeat.html" rel="nofollow noreferrer">^{<cd2>}</a>重复的次数和听写理解:</p>
<pre><code>d = {1:5, 2:2, 3:1, 4:3, 5:3}
l = df['Month'].map(d)
df = pd.DataFrame({col: np.repeat(df[col], l) for col in df.columns}, columns=df.columns)
</code></pre>
<hr/>
^{pr2}$
<p>另一个解决方案如果需要,用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.concat.html" rel="nofollow noreferrer">^{<cd3>}</a>重复所有行5次:</p>
<pre><code>df = pd.concat([df] * 5, ignore_index=True)
</code></pre>
<hr/>
<pre><code>print (df)
id Year Month Day Instant Temperature DayType DayValidity \
0 192 2008 1 5 0 8.03 6 1
1 193 2008 2 5 1 8.07 6 1
2 194 2008 3 5 2 8.10 6 1
3 195 2008 4 5 3 8.07 6 1
4 196 2008 5 5 4 8.03 6 1
5 192 2008 1 5 0 8.03 6 1
6 193 2008 2 5 1 8.07 6 1
7 194 2008 3 5 2 8.10 6 1
8 195 2008 4 5 3 8.07 6 1
9 196 2008 5 5 4 8.03 6 1
10 192 2008 1 5 0 8.03 6 1
11 193 2008 2 5 1 8.07 6 1
12 194 2008 3 5 2 8.10 6 1
13 195 2008 4 5 3 8.07 6 1
14 196 2008 5 5 4 8.03 6 1
15 192 2008 1 5 0 8.03 6 1
16 193 2008 2 5 1 8.07 6 1
17 194 2008 3 5 2 8.10 6 1
18 195 2008 4 5 3 8.07 6 1
19 196 2008 5 5 4 8.03 6 1
20 192 2008 1 5 0 8.03 6 1
21 193 2008 2 5 1 8.07 6 1
22 194 2008 3 5 2 8.10 6 1
23 195 2008 4 5 3 8.07 6 1
24 196 2008 5 5 4 8.03 6 1
LoadNette
0 53039.77133
1 52200.71569
2 51681.17260
3 51907.94746
4 50848.16566
5 53039.77133
6 52200.71569
7 51681.17260
8 51907.94746
9 50848.16566
10 53039.77133
11 52200.71569
12 51681.17260
13 51907.94746
14 50848.16566
15 53039.77133
16 52200.71569
17 51681.17260
18 51907.94746
19 50848.16566
20 53039.77133
21 52200.71569
22 51681.17260
23 51907.94746
24 50848.16566
</code></pre>