假设我有以下数据框“ A”
utilization utilization_billable
service
1 10.0 5.0
2 30.0 20.0
3 40.0 30.0
4 40.0 32.0
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我需要将其转换为以下数据框“ B”
utilization type
service
1 10.0 total
2 30.0 total
3 40.0 total
4 40.0 total
1 5.0 billable
2 20.0 billable
3 30.0 billable
4 32.0 billable
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因此,来自第一个的值将被归类为类型列,其值是total或billable。
data = {
'utilization': [10.0, 30.0, 40.0, 40.0],
'utilization_billable': [5.0, 20.0, 30.0, 32.0],
'service': [1, 2, 3, 4]
}
df = pd.DataFrame.from_dict(data).set_index('service')
print(df)
data = {
'utilization': [10.0, 30.0, 40.0, 40.0, 5.0, 20.0, 30.0, 32.0],
'service': [1, 2, 3, 4, 1, 2, 3, 4],
'type': [
'total',
'total',
'total',
'total',
'billable',
'billable',
'billable',
'billable',
]
}
df = pd.DataFrame.from_dict(data).set_index('service')
print(df)
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您可以使用pd.melt:
import pandas as pd
data = {
'utilization': [10.0, 30.0, 40.0, 40.0],
'utilization_billable': [5.0, 20.0, 30.0, 32.0],
'service': [1, 2, 3, 4]}
df = pd.DataFrame(data)
result = pd.melt(df, var_name='type', value_name='utilization', id_vars='service')
print(result)
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产量
service type utilization
0 1 utilization 10.0
1 2 utilization 30.0
2 3 utilization 40.0
3 4 utilization 40.0
4 1 utilization_billable 5.0
5 2 utilization_billable 20.0
6 3 utilization_billable 30.0
7 4 utilization_billable 32.0
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这样result.set_index('service')就可以service建立索引,但是我建议避免这样做,因为service值不是唯一的。