将列添加到由 Python 中的 for 循环计算的数据框中
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add columns to a data frame calculated by for loops in python
提问by anitasp
import re
#Creating several new colums with a for loop and adding them to the original df.
#Creating permutations for a second level of binary variables for df
for i in list_ib:
for j in list_ib:
if i == j:
break
else:
bina = df[i]*df[j]
print(i,j)
i are binary columns that belong to a data frame (df) and j are the same columns. I have calculated the multiplications each column with each column. My question is now, how do I add all the new binary product columns to the original df?
i 是属于数据框 (df) 的二进制列，j 是相同的列。我已经计算了每列与每列的乘法。我现在的问题是，如何将所有新的二进制产品列添加到原始 df 中？
I have tried:
我试过了：
df = df + df[i,j,bina]
but I am not getting the results I need. Any suggestions?
但我没有得到我需要的结果。有什么建议？
回答by Thanos
As I understand, i,j,binaare not part of your df. Build arrays for each one of those, each array element representing a 'row' and once you have all rows for i,j,binaready, then you can concatenate like this:
据我了解，i,j,bina不是您的 df 的一部分。为每一个构建数组，每个数组元素代表一个“行”，一旦你i,j,bina准备好所有行，那么你可以像这样连接：
>>> new_df = pd.DataFrame(data={'i':i, 'j':j, 'bina':bina}, columns=['i','j','bina'])
>>> pd.concat([df, new_df], axis=1)
Alternatively, once you have all data for 'i', 'j' and 'bina'collected and assuming you have the data for each of these in a separate array, you can do this:
或者，一旦您'i', 'j' and 'bina'收集了所有数据并假设您在单独的数组中拥有这些数据，您可以执行以下操作：
>>> df['i'] = i
>>> df['j'] = j
>>> df['bina'] = bina
This will work only if these three arrays have as many elements as rows in the DataFrame df.
仅当这三个数组具有与 DataFrame df 中的行一样多的元素时，这才有效。
I hope this helps!
我希望这有帮助！
回答by Matt Messersmith
Typically you add columns to a Dataframeusing its built-in __setitem__(), which you can access with []. For example:
通常，您可以Dataframe使用其内置的向 a 添加列__setitem__()，您可以使用[]. 例如：
import pandas as pd
df = pd.DataFrame()
df["one"] = 1, 1, 1
df["two"] = 2, 2, 2
df["three"] = 3, 3, 3
print df
# Output:
# one two three
# 0 1 2 3
# 1 1 2 3
# 2 1 2 3
list_ib = df.columns.values
for i in list_ib:
for j in list_ib:
if i == j:
break
else:
bina = df[i] * df[j]
df['bina_' + str(i) + '_' + str(j)] = bina # Add new column which is the result of multiplying columns i and j together
print df
# Output:
# one two three bina_two_one bina_three_one bina_three_two
# 0 1 2 3 2 3 6
# 1 1 2 3 2 3 6
# 2 1 2 3 2 3 6
