blocks|key|4298308|text|melt|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4298309|df.melt(['Type',+'Class'],+var_name='Date',+value_name='Value')

++++++Type++++++Class++++++++Date++Value
0+++Plant1++++++Plant++24/01/2018+++5498
1+++Plant2++++++Plant++24/01/2018+++3416
2+++++Veg1++Vegetable++24/01/2018+++5426
3+++++Veg2++Vegetable++24/01/2018+++5317
4+++Plant1++++++Plant++25/01/2018+++5998
5+++Plant2++++++Plant++25/01/2018+++4844
6+++++Veg1++Vegetable++25/01/2018+++5464
7+++++Veg2++Vegetable++25/01/2018+++4616
8+++Plant1++++++Plant++26/01/2018+++5815
9+++Plant2++++++Plant++26/01/2018+++4991
10++++Veg1++Vegetable++26/01/2018+++3756
11++++Veg2++Vegetable++26/01/2018+++7528|code-block|syntax|javascript|4298310|4298311|set_index+%2B+stack|4298312|(df.set_index(['Type',+'Class'])
+++.stack()
+++.rename_axis(['Type',+'Class',+'Date'])
+++.reset_index(name='Value')
)

++++++Type++++++Class++++++++Date++Value
0+++Plant1++++++Plant++24/01/2018+++5498
1+++Plant1++++++Plant++25/01/2018+++5998
2+++Plant1++++++Plant++26/01/2018+++5815
3+++Plant2++++++Plant++24/01/2018+++3416
4+++Plant2++++++Plant++25/01/2018+++4844
5+++Plant2++++++Plant++26/01/2018+++4991
6+++++Veg1++Vegetable++24/01/2018+++5426
7+++++Veg1++Vegetable++25/01/2018+++5464
8+++++Veg1++Vegetable++26/01/2018+++3756
9+++++Veg2++Vegetable++24/01/2018+++5317
10++++Veg2++Vegetable++25/01/2018+++4616
11++++Veg2++Vegetable++26/01/2018+++7528|4298313|entityMap^0|0|4|0|0|0|0|9|C|5|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@$9|S|A|T|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|U|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|V|8|@]|D|@]|E|$]]|$1|L|3|M|5|6|7|W|8|@$9|X|A|Y|B|C]|$9|Z|A|10|B|C]]|D|@]|E|$]]|$1|N|3|O|5|H|7|11|8|@]|D|@]|E|$I|J]]|$1|P|3|-4|5|6|7|12|8|@]|D|@]|E|$]]]|Q|$]]

<h3><code>melt</code></h3>
<pre><code>df.melt(['Type', 'Class'], var_name='Date', value_name='Value')

      Type      Class        Date  Value
0   Plant1      Plant  24/01/2018   5498
1   Plant2      Plant  24/01/2018   3416
2     Veg1  Vegetable  24/01/2018   5426
3     Veg2  Vegetable  24/01/2018   5317
4   Plant1      Plant  25/01/2018   5998
5   Plant2      Plant  25/01/2018   4844
6     Veg1  Vegetable  25/01/2018   5464
7     Veg2  Vegetable  25/01/2018   4616
8   Plant1      Plant  26/01/2018   5815
9   Plant2      Plant  26/01/2018   4991
10    Veg1  Vegetable  26/01/2018   3756
11    Veg2  Vegetable  26/01/2018   7528
</code></pre>
<hr />
<h3><code>set_index</code> + <code>stack</code></h3>
<pre><code>(df.set_index(['Type', 'Class'])
   .stack()
   .rename_axis(['Type', 'Class', 'Date'])
   .reset_index(name='Value')
)

      Type      Class        Date  Value
0   Plant1      Plant  24/01/2018   5498
1   Plant1      Plant  25/01/2018   5998
2   Plant1      Plant  26/01/2018   5815
3   Plant2      Plant  24/01/2018   3416
4   Plant2      Plant  25/01/2018   4844
5   Plant2      Plant  26/01/2018   4991
6     Veg1  Vegetable  24/01/2018   5426
7     Veg1  Vegetable  25/01/2018   5464
8     Veg1  Vegetable  26/01/2018   3756
9     Veg2  Vegetable  24/01/2018   5317
10    Veg2  Vegetable  25/01/2018   4616
11    Veg2  Vegetable  26/01/2018   7528
</code></pre>


<p>I am looking to transpose only certain columns in my dataframe and their values by keeping starting columns fixed.</p>

<p>I/P frame:</p>

<pre><code>Type    Class   24/01/2018  25/01/2018  26/01/2018
Plant1  Plant   5498    5998    5815
Plant2  Plant   3416    4844    4991
Veg1    Vegetable   5426    5464    3756
Veg2    Vegetable   5317    4616    7528
</code></pre>

<p>O/P frame:</p>

<pre><code>Type    Class   Value   Date
Plant1  Plant   5498    24/01/2018
Plant1  Plant   5998    25/01/2018
Plant1  Plant   5815    26/01/2018
Veg1    Vegetable   5426    24/01/2018
Veg1    Vegetable   5464    25/01/2018
Veg1    Vegetable   3756    26/01/2018
</code></pre>

<p>I normally do this in excel, and tried using pivot in pandas but unable to get an idea to implement it. Can anyone help in giving me a lead?</p>

<p>Thanks</p>


Transpose only few columns and rows from a dataframe

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我希望通过保持起始列的固定来仅转置我的数据帧中的某些列及其值。I/P帧：Type    Class   24/01/2018  25/01/2018  26/01/2018Plant1  Plant   5498    5998    5815Plant2  Plant   3416    4844    4991Ve...

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