英文:
Saving panda dataframe to csv changes values
问题
以下是您要翻译的内容：
我想将一堆数值保存到数据框中，然后将其保存为CSV文件，但在保存过程中，数值会发生变化。让我们看看最小可行性示例：
import pandas as pd
import csv
df = {
"value1": [110.589, 222.534, 390.123],
"value2": [50.111, 40.086, 45.334]
}
df.round(1)
#检查点
df.to_csv(some_path)
如果我进行调试并查看在我标记为“检查点”的步骤之后的df的值，即在四舍五入之后，它们如下：
[110.6000, 222.5000, 390.1000],
[50.1000, 40.1000, 45.3000]
实际上，我的数据框要大得多，当我保存后打开CSV文件时，一些值（通常在几十行的随机块中）已经发生了变化！它们看起来像这样：
[110.600000000001, 222.499999999999, 390.099999999999],
[50.099999999999, 40.100000000001, 45.300000000001]
因此，它总是偏离“真实”/四舍五入的值0.000000000001。有谁知道这是怎么回事/如何避免这种情况吗？
英文:
I want to save a bunch of values in a dataframe to csv but I keep running in the problem that something changes to values while saving. Let's have a look at the MWE:
import pandas as pd
import csv
df = {
"value1": [110.589, 222.534, 390.123],
"value2": [50.111, 40.086, 45.334]
}
df.round(1)
#checkpoint
df.to_csv(some_path)
If I debug it and look at the values of df at the step which I marked "checkpoint", thus after rounding, they are like
[110.6000, 222.5000, 390.1000],
[50.1000, 40.1000, 45.3000]
In reality, my data frame is much larger and when I open the csv after saving, some values (usually in a random block of a couple of dozen rows) have changed! They then look like
[110.600000000001, 222.499999999999, 390.099999999999],
[50.099999999999, 40.100000000001, 45.300000000001]
So it's always a 0.000000000001 offset from the "real"/rounded values. Does anybody know what's going on here/how I can avoid this?
答案1
得分: 2
这是一个典型的浮点数问题。 pandas 提供了定义 float_format 的选项：
df.to_csv(some_path, float_format='%.4f')
这将强制保留4位小数（或者实际上，截断到4位小数）。请注意，现在这些值将被视为字符串，因此如果在字符串上设置引用，那么这些列也将被引用。
英文:
This is a typical floating point problem. pandas gives you the option to define a float_format:
df.to_csv(some_path, float_format='%.4f')
This will force 4 decimals (or actually, does a cut-off at 4 decimals). Note that values will be treated as strings now, so if you set quoting on strings, then these columns are also quoted.
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