用NaN值迭代连接 pandas 中的列 [英] Iteratively concatenate columns in pandas with NaN values

问题描述

我有一个pandas.DataFrame数据帧:

import pandas as pd

df = pd.DataFrame({"x": ["hello there you can go home now", "why should she care", "please sort me appropriately"], 
    "y": [np.nan, "finally we were able to go home", "but what about meeeeeeeeeee"],
    "z": ["", "alright we are going home now", "ok fine shut up already"]})

cols = ["x", "y", "z"]

我想迭代地连接这些列，而不是像这样写:

I want to iteratively concatenate these columns, as opposed to writing something like:

df["concat"] = df["x"].str.cat(df["y"], sep = " ").str.cat(df["z"], sep = " ")

我知道将三列组合在一起似乎微不足道，但实际上我有30列.所以，我想做些类似的事情:

I know that three columns seems trivial to put together, but I actually have 30. so, I would like to do something like:

df["concat"] = df[cols[0]]
for i in range(1, len(cols)):
    df["concat"] = df["concat"].str.cat(df[cols[i]], sep = " ")

现在，最初的df["concat"] = df[cols[0]]行工作正常，但是位置df.loc[1, "y"]中的NaN值弄乱了串联.最终，由于该一个空值，整个1行在df["concat"]中最终以NaN结尾.我该如何解决?我需要指定pd.Series.str.cat的某些选项吗?

Right now, the initial df["concat"] = df[cols[0]] line works fine, but the NaN value in location df.loc[1, "y"] messes up the concatenation. Ultimately, the entire 1st row ends up as NaN in df["concat"] due to this one null value. How can I get around this? Is there some option with pd.Series.str.cat I need to specify?

推荐答案

选项1

Option 1

pd.Series(df.fillna('').values.tolist()).str.join(' ')

0                    hello there you can go home now  
1    why should she care finally we were able to go...
2    please sort me appropriately but what about me...
dtype: object

选项2

Option 2

df.fillna('').add(' ').sum(1).str.strip()

0                      hello there you can go home now
1    why should she care finally we were able to go...
2    please sort me appropriately but what about me...
dtype: object

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