SKU: 9046072887
ponytail palm no roots

ponytail palm no roots Ponytail Palm

Sale price$23.98 Regular price$26.64
Save 10%

Pay in installments of $6.66 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 24 - Jul 29

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

ponytail palm no roots Ponytail PalmCurly Ponytail Foliage on a Swollen Trunk Ponytail Palm is one of those plants that makes people smile at first glance. A swollen, bulbous base tapers into a slender trunk, crowned with a fountain of long, ribbon like leaves that spill over the sides like a green ponytail. Despite its common name, it isnt a true palm at all, but a caudex forming succulent native to Mexico, which has evolved to store water in its thick base. The look is part desert

Curly “Ponytail” Foliage on a Swollen Trunk

Ponytail Palm is one of those plants that makes people smile at first glance. A swollen, bulbous base tapers into a slender trunk, crowned with a fountain of long, ribbon-like leaves that spill over the sides like a green ponytail. Despite its common name, it isn’t a true palm at all, but a caudex-forming succulent native to Mexico, which has evolved to store water in its thick base. The look is part desert sculpture, part whimsical houseplant, and it fits just as well on a sunny windowsill as it does styled on a plant stand.

Slow, Compact Growth, and Long-Lived

Indoors, Ponytail Palm is slow-growing, which makes it a fantastic long-term companion plant. Young plants have a single trunk and a tight tuft of foliage, while older specimens gradually thicken their base and may branch into multiple heads over time. In containers inside the home, most plants typically top out at around 3–4 feet tall, although very old specimens in large pots can reach 5–6 feet. Because it grows slowly and stays relatively narrow, it’s easy to tuck into corners, tabletops, or grouped displays without worrying that it will outgrow the space overnight.

Bright Light and Infrequent Watering is all it requires

Think of Ponytail Palm as more of a succulent than a palm when it comes to care. It thrives in bright, indirect light and happily basks in a bit of gentle direct sun, especially morning or late-afternoon rays. A bright east or south window is ideal; in lower light, it will survive, but growth slows dramatically, and the trunk may elongate rather than stay stout. Plant it in a very well-draining mix—such as cactus or succulent soil, or potting mix heavily amended with sand and perlite—so that excess water runs through quickly and never lingers around the roots.

Watering is where Ponytail Palm really earns its “set it and forget it” reputation. The caudex stores water, so you’ll want to let the soil dry out completely between waterings, then soak thoroughly and drain well. In most indoor settings, that means watering every 2–4 weeks, less in low light or winter, and a bit more in bright, warm conditions. It prefers typical household temperatures of around 65–80°F and average humidity, shrugging off dry indoor air that would bother more finicky tropicals. Overwatering is just about the only way to truly get into trouble with this plant—if the base ever feels soft or the leaves pull out easily, it’s a sign the roots have stayed wet too long.

Pet-Safe Personality Plant for Home or Office

In the “indoor landscape,” Ponytail Palm is pure personality. Use it as a quirky focal point on a plant shelf, as a sculptural accent on a low stool, or lined up in multiples for a desert-inspired vignette. It pairs beautifully with cacti, snake plants, and other drought-tolerant houseplants, adding a softer, playful texture to an otherwise spiky or architectural grouping. And because it’s considered non-toxic to cats, dogs, and even horses, you can relax a bit if curious paws can’t resist playing with those tempting, dangling leaves.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 9046072887

Discover Niche Categories That Outsell ponytail palm no roots

Top-Converting Item to Boost Your Average Order

4.4 ★★★★★
Based on 27 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
A
Verified Purchase
Amazon Customer
Omaha, US
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
K
Verified Purchase
Kindle Customer
Lexington, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Los Angeles, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Battle Creek, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 1, 2022
G
Verified Purchase
Gabe Rigall
Whiting, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022

recommand products