SKU: 24468898670
fan palm indoor plant

fan palm indoor plant Ruffled Fan Palm (Licuala grandis) – Exotic Elegance for Your Garden

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Description

fan palm indoor plant Ruffled Fan Palm (Licuala grandis) – Exotic Elegance for Your GardenRuffled Fan Palm: Sculptural Beauty for Your Home or Outdoor Oasis The Ruffled Fan Palm (Licuala grandis) brings instant sophistication, whether as a bold indoor statement piece or an elegant addition to your outdoor retreat. Its broad, circular, pleated leaves create a dramatic, rippling effect, making it one of the most visually striking palms you can own. Nationwide Plants offers large plant sizes of this Palm Variety. Unlike many palms that

Ruffled Fan Palm: Sculptural Beauty for Your Home or Outdoor Oasis

The Ruffled Fan Palm (Licuala grandis) brings instant sophistication, whether as a bold indoor statement piece or an elegant addition to your outdoor retreat. Its broad, circular, pleated leaves create a dramatic, rippling effect, making it one of the most visually striking palms you can own. Nationwide Plants offers large plant sizes of this Palm Variety. 

Unlike many palms that require full sun and vast spaces, this compact, shade-loving variety thrives indoors as a houseplant or outdoors in tropical and subtropical gardens. Whether placed in a decorative container in your living room or nestled into a lush patio arrangement, the Ruffled Fan Palm adds an exotic, refined touch.

Plant Details

  • Mature Height: 6–10 feet (shorter indoors)
  • Mature Width: 5–6 feet
  • Sun Exposure: Partial shade, dappled sunlight
  • Botanical Name: Licuala grandis
  • Other Common Names: Vanuatu Fan Palm, Palas Palm

Why Choose the Ruffled Fan Palm?

A Showstopping Indoor Plant

Looking for a statement plant that doesn’t require full sun? The Ruffled Fan Palm is perfect for indoor spaces, thriving in bright, indirect light. Its dramatic, fan-shaped leaves add a sculptural, high-end look to living rooms, offices, and even bathrooms where humidity is higher.

Pair it with modern, minimalist decor for a striking contrast, or complement tropical or bohemian styles with its rich, deep-green fronds. Unlike many palms that grow tall and spindly indoors, this one stays compact and maintains a lush, full shape.

Low-Maintenance Elegance

Despite its delicate, pleated leaves, the Ruffled Fan Palm is surprisingly easy to care for. Whether indoors or outdoors, it requires minimal pruning, resists most common palm pests, and adapts well to container life. Indoors, it acts as a natural air purifier, helping to create a fresher, healthier environment.

Shade-Loving and Versatile

Unlike many palm species that crave direct sunlight, the Ruffled Fan Palm actually prefers partial shade. This makes it ideal for:

Indoors: Near east- or north-facing windows, where it receives filtered light.
Outdoors: Covered patios, shaded gardens, or under taller trees.

Compact Yet Striking

Standing at 6–10 feet outdoors and smaller when grown indoors, this palm fits beautifully into a variety of spaces without overwhelming them. It’s perfect for smaller urban patios, cozy garden nooks, or as a stunning houseplant in homes where space is limited but style is not.

A Cleaner, More Refined Palm

Tired of palms that shed messy fronds? The Ruffled Fan Palm holds onto its leaves longer than other species, making it a lower-maintenance option for both indoor and outdoor spaces.

How to Grow and Care for Your Ruffled Fan Palm

Light Requirements

  • Indoors: Prefers bright, indirect light. Can tolerate low light but may grow more slowly.
  • Outdoors: Partial shade or dappled sunlight is best. Avoid harsh afternoon sun, which can scorch leaves.

Watering Needs

  • Keep soil consistently moist but not soggy.
  • Indoors: Water when the top inch of soil feels dry. Increase humidity with a pebble tray or occasional misting.
  • Outdoors: Water regularly, especially in warmer months. Reduce watering slightly in cooler months.

Soil Preferences

  • Prefers rich, well-draining soil.
  • For indoor plants, use a mix of peat, sand, and compost to maintain moisture without waterlogging.

Temperature and Humidity

  • Indoors: Prefers warm, humid conditions (65–80°F). Keep away from cold drafts or vents.
  • Outdoors: Hardy in USDA Zones 10–11. Cannot tolerate frost—bring potted plants inside if temperatures drop below 50°F.

Fertilizing

  • Feed every 2–3 months with a balanced, slow-release palm fertilizer.
  • Indoor plants benefit from occasional liquid seaweed or fish emulsion to enhance leaf vibrancy.

Pruning and Maintenance

  • Minimal pruning needed—just remove any brown or damaged leaves as they appear.
  • If grown indoors, occasionally wipe leaves with a damp cloth to remove dust and help the plant absorb more light.

Where the Ruffled Fan Palm Shines

As an Indoor Houseplant

  • Living Rooms & Offices: A stunning floor plant that commands attention.
  • Bathrooms & Kitchens: Thrives in naturally humid areas.
  • Bedrooms: Adds a calming, tropical touch while subtly purifying the air.

Outdoor Uses

  • Patios & Poolside Spaces: Brings a resort-like feel in a decorative pot.
  • Tropical Garden Feature: Pairs beautifully with ferns, bromeliads, and elephant ears.
  • Entryway Accent: A pair of potted Ruffled Fan Palms creates a grand entrance.
  • Shade-Loving Border Plant: Adds softness and texture along pathways.

Why This Palm Stands Out

Compared to more common indoor palms like the Majesty or Areca Palm, the Ruffled Fan Palm offers:
A more compact, symmetrical shape—no lanky, leggy growth.
Low-maintenance beauty—less pruning and fewer dropped fronds.
Thrives in lower light—perfect for shaded patios and indoor spaces.
A cleaner look—no messy leaf shedding like other palms.

Bring the Tropics to Your Home

Whether you want to elevate your indoor plant collection with a striking, sculptural palm or create a lush, shaded garden escape, the Ruffled Fan Palm is the perfect choice. With its gorgeous pleated leaves, compact size, and easy-care nature, this unique palm is a must-have for plant lovers who appreciate both beauty and practicality.

Shipping Notes
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SKU: 24468898670

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Hashi Hanta
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Excelllent book
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As one of the group of Native Americans who landed on Alcatraz with Richard Oakes, I enjoyed this book. Richard was a fantastic man. A good man.
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Reviewed in the United States on February 14, 2019
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Carnegie, US
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The truth about the Native people. THANK YOU Kent for writing this book. We purchased about 12 total.
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Walter Echo-Hawk, author of THE SEA OF GRASS.
Lexington, US
★★★★★ 5
Native American history at its best!
Format: Hardcover
Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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Natrona Heights, US
★★★★★ 5
Excellent book on ML
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This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents. The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!! The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!! I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge. Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents. Personally I was disappointed by lack of any example on time series. Must have for ML practitioner as a reference and guide.
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Reviewed in the United States on December 20, 2024
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Richard Hackathorn
Battle Creek, US
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Excellent Textbook for Hands-On Learning of ML
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This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book. For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch. For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min). From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures. I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications. Several textbook editions later, what is different about this new edition? First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills. Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like. Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
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Reviewed in the United States on February 26, 2022

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