blocks|key|3135018|text|试试这个：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3135019|import+pandas+as+pd
inp+=+[{'a1':'Juancito+1'},+{'a1':'Juancito+2'},+{'a1':'Juancito+3'}]
df+=+pd.DataFrame(inp)

for+i+in+range(df["a1"].shape[0]):
++++print(i)
++++if+'Juancito'+in+df["a1"][i]:
++++++++df["a1"][i]+=+'Juancito'
++++else:
++++++++pass
df.head()|code-block|syntax|javascript|3135020|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

Try this:
<pre><code>import pandas as pd
inp = [{'a1':'Juancito 1'}, {'a1':'Juancito 2'}, {'a1':'Juancito 3'}]
df = pd.DataFrame(inp)

for i in range(df[&quot;a1&quot;].shape[0]):
 print(i)
 if 'Juancito' in df[&quot;a1&quot;][i]:
 df[&quot;a1&quot;][i] = 'Juancito'
 else:
 pass
df.head()
</code></pre>

blocks|key|2296185|text|您没有在代码中设置dataframe元素的值。您只是暂时将其分配给i。一种方法是使用数字索引，其中行号将随i而改变，列号将是您想要处理的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2296186|示例：|2296187|import+pandas+as+pd
inp+=+[{'a1':'Juancito+1'},+{'a1':'Juancito+2'},+{'a1':'Juancito+3'}]
df+=+pd.DataFrame(inp)

for+i+in+range(len(df)):
++++if+'Juancito'+in+df.iloc[i][0]:
++++++++df.iloc[i][0]+=+'Juancito'
++++else:
++++++++pass
df.head()|code-block|syntax|javascript|2296188|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|K|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|L|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|M|8|@]|9|@]|A|$G|H]]|$1|I|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|J|$]]

You are not setting the value of the dataframe element in your code. You are just assigning it temporarily to i.
One approach would be to use numeric indexing where row number will change with i and column number would be the one you want to process.
Example:
<pre><code>import pandas as pd
inp = [{'a1':'Juancito 1'}, {'a1':'Juancito 2'}, {'a1':'Juancito 3'}]
df = pd.DataFrame(inp)

for i in range(len(df)):
 if 'Juancito' in df.iloc[i][0]:
 df.iloc[i][0] = 'Juancito'
 else:
 pass
df.head()
</code></pre>

blocks|key|3135058|text|正如评论中提到的，将更改合并在一起。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3135059|import+pandas+as+pd
inp+=+[{'a1':'Juancito+1'},+{'a1':'Juancito+2'},+{'a1':'Juancito+3'}]
df+=+pd.DataFrame(inp)

for+index,+i+in+enumerate(df['a1'])::
++++if+'Juancito'+==+i:
++++++++df['a1'].loc[index]+=+'Juancito'
++++else:
++++++++pass
df.head()|code-block|syntax|javascript|3135060|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

As mentioned in the comment, incorporated the changes
<pre class="lang-py prettyprint-override"><code>import pandas as pd
inp = [{'a1':'Juancito 1'}, {'a1':'Juancito 2'}, {'a1':'Juancito 3'}]
df = pd.DataFrame(inp)

for index, i in enumerate(df['a1'])::
 if 'Juancito' == i:
 df['a1'].loc[index] = 'Juancito'
 else:
 pass
df.head()
</code></pre>

blocks|key|3135071|text|你不需要一个for+循环.|type|unstyled|depth|inlineStyleRanges|offset|length|style|BOLD|CODE|entityRanges|data|3135072|只需将numpy.where与Series.str.contains结合使用|3135073|In+[83]:+import+numpy+as+np

In+[84]:+df['a1']+=+np.where(df['a1'].str.contains('Juancito'),+'Juancito',+df['a1'])

In+[85]:+df
Out[85]:+
+++++++++a1
0++Juancito
1++Juancito
2++Juancito|code-block|syntax|javascript|3135074|entityMap|0|LINK|mutability|MUTABLE|url|https://numpy.org/doc/stable/reference/generated/numpy.where.html|1|https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.contains.html^0|6|3|A|3|6|3|0|3|B|F|J|3|B|0|F|J|1|0|0^^$0|@$1|2|3|4|5|6|7|X|8|@$9|Y|A|Z|B|C]|$9|10|A|11|B|C]|$9|12|A|13|B|D]]|E|@]|F|$]]|$1|G|3|H|5|6|7|14|8|@$9|15|A|16|B|D]|$9|17|A|18|B|D]]|E|@$9|19|A|1A|1|1B]|$9|1C|A|1D|1|1E]]|F|$]]|$1|I|3|J|5|K|7|1F|8|@]|E|@]|F|$L|M]]|$1|N|3|-4|5|6|7|1G|8|@]|E|@]|F|$]]]|O|$P|$5|Q|R|S|F|$T|U]]|V|$5|Q|R|S|F|$T|W]]]]

You don't need a <code>for</code> loop.
Just use <a href="https://numpy.org/doc/stable/reference/generated/numpy.where.html" rel="nofollow noreferrer"><code>numpy.where</code></a> with <a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.contains.html" rel="nofollow noreferrer"><code>Series.str.contains</code></a>:
<pre><code>In [83]: import numpy as np

In [84]: df['a1'] = np.where(df['a1'].str.contains('Juancito'), 'Juancito', df['a1'])

In [85]: df
Out[85]: 
 a1
0 Juancito
1 Juancito
2 Juancito
</code></pre>

how are you? I'm pretty new at code, and I have this question:
I want to iterate through a column, and I want to change this column values based on a condition, in this case, I want to change very value from column 'a1': if the value contains the word 'Juancito' I want to change it to just 'Juancito'.
The for loop works OK, but the value doesn't change in the end.
What I'm doing wrong?
<pre><code>import pandas as pd
inp = [{'a1':'Juancito 1'}, {'a1':'Juancito 2'}, {'a1':'Juancito 3'}]
df = pd.DataFrame(inp)

for i in df['a1']:
 if 'Juancito' in i:
 i = 'Juancito'
 else:
 pass
df.head()
</code></pre>

Python Pandas change values from a condition

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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你好吗？我在密码方面很新，我有个问题：我想迭代一列，并且我想根据一个条件来更改这个列的值，在这种情况下，我想从‘A1’栏中更改非常值:如果值包含'Juancito‘这个词，我想将它更改为'Juancito’。for循环工作正常，但值在最后没有变化。我做错什么了？import pandas as pdinp = [{'a...

问Python从条件中更改值
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