我有一个pandas数据集,其中有一列单词和一列整数(0,1)。出现在零(第一个整数或1之后)和1(包括1)之间的所有单词都应放入2D数组中。
让我解释一下:
考虑此熊猫数据框:
import pandas as pd
df = pd.DataFrame(columns=['Text','Selection_Values'])
df["Text"] = ["Hi", "this is", "just", "a", "single", "sentence.", "This", "is another one."]
df["Selection_Values"] = [0,0,0,0,0,1,0,1]
print(df)
这是示例数据集:
Text Selection_Values
0 Hi 0
1 this is 0
2 just 0
3 a 0
4 single 0
5 sentence. 1
6 This 0
7 is another one. 1
预期结果应该是:
[["Hi this is just a single sentence."],["This is another one"]]
您对此有任何想法吗?
这是我到目前为止所做的:
result = []
s = ""
for i in range(len(df["Text"])):
s += df["Text"][i] + " "
if df["Selection_Values"][i] == 1:
result.append([s])
s = ""
有效:
[['Hi this is just a single sentence. '], ['This is another one. ']]
...但这可能不是最佳方法。它根本没有使用熊猫框架。
答案 0 :(得分:3)
使用shift
+ ' '.join
。当然,这是假设每个句子都有一个结束1
,并且没有悬挂的句子。
g = df['Selection_Values'].shift().eq(1).cumsum()
df['Text'].groupby(g).agg(' '.join).tolist()
['Hi this is just a single sentence.', 'This is another one.']
答案 1 :(得分:2)
这是一种可能的方法:
import pandas as pd
# Initialize example dataframe
df = pd.DataFrame(columns=['Text', 'Selection_Values'])
df["Text"] = ["Hi", "this is", "just", "a", "single", "sentence.", "This", "is another one."]
df["Selection_Values"] = [0, 0, 0, 0, 0, 1, 0, 1]
# Add column with an unique group ID for each sentence
df['group_id'] = df.Selection_Values.shift(1, fill_value=0).cumsum()
# Join the strings that have the same group ID
sentence_series = df.groupby('group_id')['Text'].agg(' '.join)
# Optional: convert result series to list
sentence_list = sentence_series.to_list()
print(sentence_list)
# Output:
# ['Hi this is just a single sentence.', 'This is another one.']
答案 2 :(得分:2)
使用numpy.split
+ Series.str.cat
单线:
In [143]: [[s.str.cat(sep=' ')] for s in np.split(df.Text, df[df.Selection_Values == 1].index+1) if not s.empty]
Out[143]: [['Hi this is just a single sentence.'], ['This is another one.']]