(GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format = ewma(x**2) -ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

(GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format = ewma(x**2) -ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

(GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

(GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

(GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . (For ?? = 1, this reduces

ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (∑t i=0 wi )2 (∑t i=0 wi )2 − ∑t i=0 w2 i . (For wi = 1, this reduces to

ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . 672 Chapter 3. User Guide (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format

ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . 4.11. Computational tools (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) 2480 Chapter 8. Release Notes pandas: powerful Python

ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . 4.11. Computational tools (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) 8.7. Version 0.19 2485 pandas: powerful Python data analysis

ewma(x**2) - ewma(x)**2; whereas if bias=False (the default), the biased variance statistics are scaled by debiasing factors (︁∑︀? ?=0 ?? )︁2 (︁∑︀? ?=0 ?? )︁2 − ∑︀? ?=0 ?2 ? . 2.12. Computational tools (GH13522) • Bug in matplotlib AutoDataFormatter; this restores the second scaled formatting and re-adds micro-second scaled formatting (GH13131) • Bug in selection from a HDFStore with a fixed format