将 pandas 列中的整数值转换为字符串

Question

我有一个示例数据如下：

datetime    x   y
2021-05-01. 25. val1
2021-05-02. 50. val2
2021-05-03. 100 val3
2021-05-04. 25.  val4
2021-05-05. 100. val5
2021-05-06. 50.  val6

我想创建一个新列 calle z，它将 25 映射到低，将 50 映射到中，将 100 映射到高，预期输出如下所示：

datetime    x   y.     z
2021-05-01. 25. val1.  Low
2021-05-02. 50. val2.  Medium
2021-05-03. 100 val3.  High
2021-05-04. 25.  val4. Low
2021-05-05. 100. val5. High
2021-05-06. 50.  val6. Medium

Answer 1

你可以使用 numpy select:

conditions = [df['x'] == 25, df['x'] == 50, df['x'] == 100]
choices = ['Low', 'Medium', 'High']

df['z'] = np.select(conditions, choices)

输出：

       datetime    x       y       z
0   2021-05-01.   25.  val1.     Low
1   2021-05-02.   50.  val2.  Medium
2   2021-05-03.  100.  val3.    High
3   2021-05-04.   25.  val4.     Low
4   2021-05-05.  100.  val5.    High
5   2021-05-06.   50.  val6.  Medium

如果格式为字符串，请使用：

conditions = [df['x'] == '25.', df['x'] == '50.', df['x'] == '100.']

Answer 2

pandas

中有四种整数转字符串的方法

1: frame[‘DataFrame Column’]= frame[‘DataFrame Column’].map(str)

2: frame[‘DataFrame Column’]= frame[‘DataFrame Column’].apply(str)

3: frame[‘DataFrame Column’]= frame[‘DataFrame Column’].astype(str)

4: frame[‘DataFrame Column’]= frame[‘DataFrame Column’].values.astype(str)

Answer 3

您可以使用地图：

d = {25:'Low',50:'Medium',100:'high'}
df['z'] = df['x'].map(d)

#       datetime      x     y       z
# 0  2021-05-01.   25.0  val1     Low
# 1  2021-05-02.   50.0  val2  Medium
# 2  2021-05-03.  100.0  val3    high
# 3  2021-05-04.   25.0  val4     Low
# 4  2021-05-05.  100.0  val5    high
# 5  2021-05-06.   50.0  val6  Medium

将 pandas 列中的整数值转换为字符串

Converting an integer value in pandas column to string

python

numpy

pandas

data-science