我正在使用一个多索引数据帧,并希望执行一些我正在努力解决的操作:
a)我想对一个列表应用几个操作(按元素),而不使用for循环
b)我想提取我的数据帧的索引值并比较这些值;然后再将它们从object转换为int或float
c)我想比较DataFrame中的值(不使用for循环),并根据比较的值从任一列中选择值
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import pandas as pd
import numpy as np
idx = pd.IndexSlice
ix = pd.MultiIndex.from_product(
[['2015', '2016', '2017', '2018'],
['2016', '2017', '2018', '2019', '2020'],
['A', 'B', 'C']],
names=['SimulationStart', 'ProjectionPeriod', 'Group']
)
df = pd.DataFrame(np.random.randn(60, 1), index=ix, columns=['Origin'])
origin = df.loc[idx[:, :, :], 'Origin'].values
increase_over_base_percent = 0.3
increase_over_base_abs = 10
abs_level = 1
min_increase = 0.001
'Is there a way to do this comparison without using for loops?'
# The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
change = pd.Series(np.nan)
i = 0
for element in origin:
change[i] = max(
min(element * (1 + increase_over_base_percent),
element + increase_over_base_abs,
abs_level),
element + min_increase)
i += 1
print(change)
# Write results to a new column in the DataFrame ('Change')
df.loc[idx[:, :, :], 'Change'] = change
# Add data on 'Group' level
group_qualifier = [0, 0, 1]
# Is there a way to apply the group_qualifier to the group level without having to slice each index?
# Note: the formula does not work yet (results are to be reported in a new column of the DataFrame)
df.loc[idx[:], 'GroupQA'] = group_qualifier
'This is the part I am struggling with most (my index values are objects, not integers or floats;'
'and the comparison of values within the DataFrame does not work either)'
# Create new column 'Selected'; use origin values for all combinations where
# projectionPeriod < simulationStart & group_qualifier value == 0;
# use change values for all other combinations
values = df.index.get_level_values
mask = (values('ProjectionPeriod') - values('SimulationStart')) <= 1
mask = mask * df.loc[idx[:], 'GroupQA'].values
selected = df.loc[mask]
df.loc[idx[:, :, :], 'Selected'] = selected
A的部分答案:
我们的想法是直接在
Origin
系列上使用pandas的min
和max
函数(稍微扭曲一下,使用clip
表示abs_level
)。你知道吗由于操作保留索引,因此可以直接将结果分配给列。你知道吗
编辑:如果您愿意,您可以使用
combine
方法,该方法在this question结尾解释。你知道吗相关问题 更多 >
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