如何对一列中值低于负数的数据帧的行进行子集化？

Question

我有一个 51077 行 × 4 列的数据框。 我需要在第三列中使用值 > 0.3 和 < -0.3 的行对数据框进行子集化。

我使用了以下内容：

df_filtered = df[np.logical_and(df["third column"] > 0.3, df["third column"] < -0.3)]

但结果只显示列名

我也试过：

df_filtered = df.query("third column < -0.3 & third column > 0.3")

结果还是一样

我该如何解决这个问题？

Answer 1

你快明白了：

df_filtered = df.loc[(df['third column'] > 0.3) | (df['third column'] < -0.3)]

或

df_filtered = df[(df['third column'] > 0.3) | (df['third column'] < -0.3)]

Answer 2

您也可以使用 between 并反转结果：

df_filtered = df[~df['third_column'].between(-0.3, 0.3)]

示例：

>>> df
   third_column
0     -0.190030
1     -0.205187
2     -0.066776
3     -0.264480
4      0.064962
5      0.024708
6     -0.354629  # Want to keep
7     -0.180228
8      0.261640
9      0.315986  # Want to keep

>>>  df[~df['third_column'].between(-0.3, 0.3)]
   third_column
6     -0.354629
9      0.315986