在 Pandas DataFrame Python 中添加新列
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Add new column in Pandas DataFrame Python
提问by Santiago Munez
I have dataframe in Pandas for example:
例如，我在 Pandas 中有数据框：
Col1 Col2
A 1
B 2
C 3
Now if I would like to add one more column named Col3 and the value is based on Col2. In formula, if Col2 > 1, then Col3 is 0, otherwise would be 1. So, in the example above. The output would be:
现在，如果我想再添加一个名为 Col3 的列，并且该值基于 Col2。在公式中，如果 Col2 > 1，则 Col3 为 0，否则为 1。因此，在上面的示例中。输出将是：
Col1 Col2 Col3
A 1 1
B 2 0
C 3 0
Any idea on how to achieve this?
关于如何实现这一目标的任何想法？
采纳答案by Viktor Kerkez
You just do an opposite comparison. if Col2 <= 1. This will return a boolean Series with Falsevalues for those greater than 1 and Truevalues for the other. If you convert it to an int64dtype, Truebecomes 1and Falsebecome 0,
你只是做一个相反的比较。if Col2 <= 1. 这将返回一个布尔系列，False其中包含大于 1 的True值和另一个的值。如果您将其转换为int64dtype，则True变成1和False变成0，
df['Col3'] = (df['Col2'] <= 1).astype(int)
If you want a more general solution, where you can assign any number to Col3depending on the value of Col2you should do something like:
如果你想要一个更通用的解决方案，你可以Col3根据Col2你的值分配任何数字，你应该这样做：
df['Col3'] = df['Col2'].map(lambda x: 42 if x > 1 else 55)
Or:
或者：
df['Col3'] = 0
condition = df['Col2'] > 1
df.loc[condition, 'Col3'] = 42
df.loc[~condition, 'Col3'] = 55
回答by Tony Rollett
The easiest way that I found for adding a column to a DataFrame was to use the "add" function. Here's a snippet of code, also with the output to a CSV file. Note that including the "columns" argument allows you to set the name of the column (which happens to be the same as the name of the np.array that I used as the source of the data).
我发现向 DataFrame 添加列的最简单方法是使用“添加”函数。这是一段代码，还有输出到 CSV 文件。请注意，包含“columns”参数允许您设置列的名称（恰好与我用作数据源的 np.array 的名称相同）。
# now to create a PANDAS data frame
df = pd.DataFrame(data = FF_maxRSSBasal, columns=['FF_maxRSSBasal'])
# from here on, we use the trick of creating a new dataframe and then "add"ing it
df2 = pd.DataFrame(data = FF_maxRSSPrism, columns=['FF_maxRSSPrism'])
df = df.add( df2, fill_value=0 )
df2 = pd.DataFrame(data = FF_maxRSSPyramidal, columns=['FF_maxRSSPyramidal'])
df = df.add( df2, fill_value=0 )
df2 = pd.DataFrame(data = deltaFF_strainE22, columns=['deltaFF_strainE22'])
df = df.add( df2, fill_value=0 )
df2 = pd.DataFrame(data = scaled, columns=['scaled'])
df = df.add( df2, fill_value=0 )
df2 = pd.DataFrame(data = deltaFF_orientation, columns=['deltaFF_orientation'])
df = df.add( df2, fill_value=0 )
#print(df)
df.to_csv('FF_data_frame.csv')
