Thanks Olivier.<br><br>Chao<br><br><div class="gmail_quote">2011/10/7 Olivier Delalleau <span dir="ltr">&lt;<a href="mailto:shish@keba.be">shish@keba.be</a>&gt;</span><br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
You can use numpy.isnan(array).sum()<br><br>-=- Olivier<br><br><div class="gmail_quote">2011/10/7 Chao YUE <span dir="ltr">&lt;<a href="mailto:chaoyuejoy@gmail.com" target="_blank">chaoyuejoy@gmail.com</a>&gt;</span><br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div><div></div><div class="h5">
The data is read from a .mat file. <br><div><div></div><div><br><div class="gmail_quote">2011/10/7 Chao YUE <span dir="ltr">&lt;<a href="mailto:chaoyuejoy@gmail.com" target="_blank">chaoyuejoy@gmail.com</a>&gt;</span><br>

<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
Dear all, <br><br>I have an ndarray with dimension of 4X62500. is there anyway I can count the number of missing value (NaN)? because I want to know how many observations are missing?<br><br>Thanks for any idea,<br><br>Chao<br clear="all">


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<div>Chao YUE<br>Laboratoire des Sciences du Climat et de l&#39;Environnement (LSCE-IPSL)<br>UMR 1572 CEA-CNRS-UVSQ<br>Batiment 712 - Pe 119<br>91191 GIF Sur YVETTE Cedex</div>
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<div>Chao YUE<br>Laboratoire des Sciences du Climat et de l&#39;Environnement (LSCE-IPSL)<br>UMR 1572 CEA-CNRS-UVSQ<br>Batiment 712 - Pe 119<br>91191 GIF Sur YVETTE Cedex</div>
<div>Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16<br></div>

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<div>Chao YUE<br>Laboratoire des Sciences du Climat et de l&#39;Environnement (LSCE-IPSL)<br>UMR 1572 CEA-CNRS-UVSQ<br>Batiment 712 - Pe 119<br>91191 GIF Sur YVETTE Cedex</div>
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