pandas – filter で条件で行を抽出する方法

概要

説明をかく

pandas.eval

pandas.eval(expr, parser='pandas', engine: Union[str, NoneType] = None, truediv=<object object at 0x7f5374a06320>, local_dict=None, global_dict=None, resolvers=(), level=0, target=None, inplace=False)

引数

名前	型	デフォルト値
expr	str
expr	The expression to evaluate. This string cannot contain any Pythonstatements,only Python expressions.
parser	{‘pandas’, ‘python’}	‘pandas’
parser	The parser to use to construct the syntax tree from the expression. Thedefault of ‘pandas’ parses code slightly different than standardPython. Alternatively, you can parse an expression using the’python’ parser to retain strict Python semantics. See theenhancing performance documentation formore details.
engine	{‘python’, ‘numexpr’}	‘numexpr’
engine	The engine used to evaluate the expression. Supported engines areNone : tries to use numexpr, falls back to python’numexpr’: This default engine evaluates pandas objects usingnumexpr for large speed ups in complex expressionswith large frames.’python’: Performs operations as if you had eval’d in toplevel python. This engine is generally not that useful.More backends may be available in the future.
truediv	bool, optional
truediv	Whether to use true division, like in Python >= 3.deprecated:: 1.0.0
local_dict	dict or None, optional
local_dict	A dictionary of local variables, taken from locals() by default.
global_dict	dict or None, optional
global_dict	A dictionary of global variables, taken from globals() by default.
resolvers	list of dict-like or None, optional
resolvers	A list of objects implementing the __getitem__ special method thatyou can use to inject an additional collection of namespaces to use forvariable lookup. For example, this is used in thequery() method to inject theDataFrame.index and DataFrame.columnsvariables that refer to their respective DataFrameinstance attributes.
level	int, optional
level	The number of prior stack frames to traverse and add to the currentscope. Most users will not need to change this parameter.
target	object, optional	None
target	This is the target object for assignment. It is used when there isvariable assignment in the expression. If so, then target mustsupport item assignment with string keys, and if a copy is beingreturned, it must also support .copy().
inplace	bool	False
inplace	If target is provided, and the expression mutates target, whetherto modify target inplace. Otherwise, return a copy of target withthe mutation.

返り値

名前	説明
ndarray, numeric scalar, DataFrame, Series

例外

名前	説明
ValueError	There are many instances where such an error can be raised: target=None, but the expression is multiline. The expression is multiline, but not all them have item assignment. An example of such an arrangement is this: a = b + 1 a + 2 Here, there are expressions on different lines, making it multiline, but the last line has no variable assigned to the output of a + 2. inplace=True, but the expression is missing item assignment. Item assignment is provided, but the target does not support string item assignment. Item assignment is provided and inplace=False, but the target does not support the .copy() method

名前

説明

ValueError

There are many instances where such an error can be raised: target=None, but the expression is multiline. The expression is multiline, but not all them have item assignment. An example of such an arrangement is this: a = b + 1 a + 2 Here, there are expressions on different lines, making it multiline, but the last line has no variable assigned to the output of a + 2. inplace=True, but the expression is missing item assignment. Item assignment is provided, but the target does not support string item assignment. Item assignment is provided and inplace=False, but the target does not support the .copy() method

サンプルコード

In [1]:

import pandas as pd
from IPython.display import display

df = pd.DataFrame({"A": range(1, 6), "B": range(10, 0, -2)})
display(df)

	A	B
0	1	10
1	2	8
2	3	6
3	4	4
4	5	2

In [2]:

print(df.eval("A + B"))

0    11
1    10
2     9
3     8
4     7
dtype: int64

In [3]:

print(df.eval("C = A ** 2"))

   A   B   C
0  1  10   1
1  2   8   4
2  3   6   9
3  4   4  16
4  5   2  25

In [4]:

df.eval("C = A ** 2", inplace=True)
df

	A	B	C
0	1	10	1
1	2	8	4
2	3	6	9
3	4	4	16
4	5	2	25

pandas.DataFrame.eval

pandas.DataFrame.eval は、

DataFrame.eval(self, expr, inplace=False, **kwargs)

引数

名前	型	デフォルト値
expr	str
expr	The expression string to evaluate.
inplace	bool	False
inplace	If the expression contains an assignment, whether to perform theoperation inplace and mutate the existing DataFrame. Otherwise,a new DataFrame is returned.
**kwargs
**kwargs	See the documentation for eval() for complete detailson the keyword arguments accepted byquery().