load(file[, mmap_mode, allow_pickle, ...])
Load arrays or pickled objects from .npy, .npz or pickled files.
save(file, arr[, allow_pickle, fix_imports])
Save an array to a binary file in NumPy .npy format.
savez(file, *args[, allow_pickle])
Save several arrays into a single file in uncompressed .npz format.
savez_compressed(file, *args[, allow_pickle])
Save several arrays into a single file in compressed .npz format.
lib.npyio.NpzFile(fid)
A dictionary-like object with lazy-loading of files in the zipped archive provided on construction.
The format of these binary file types is documented in numpy.lib.format
loadtxt(fname[, dtype, comments, delimiter, ...])
Load data from a text file.
savetxt(fname, X[, fmt, delimiter, newline, ...])
Save an array to a text file.
genfromtxt(fname[, dtype, comments, ...])
Load data from a text file, with missing values handled as specified.
fromregex(file, regexp, dtype[, encoding])
Construct an array from a text file, using regular expression parsing.
fromstring(string[, dtype, count, like])
A new 1-D array initialized from text data in a string.
ndarray.tofile(fid[, sep, format])
Write array to a file as text or binary (default).
Return the array as an a.ndim-levels deep nested list of Python scalars.
fromfile(file[, dtype, count, sep, offset, like])
Construct an array from data in a text or binary file.
ndarray.tofile(fid[, sep, format])
Write array to a file as text or binary (default).
String formatting#array2string(a[, max_line_width, precision, ...])
Return a string representation of an array.
array_repr(arr[, max_line_width, precision, ...])
Return the string representation of an array.
array_str(a[, max_line_width, precision, ...])
Return a string representation of the data in an array.
format_float_positional(x[, precision, ...])
Format a floating-point scalar as a decimal string in positional notation.
format_float_scientific(x[, precision, ...])
Format a floating-point scalar as a decimal string in scientific notation.
Memory mapping files#memmap(filename[, dtype, mode, offset, ...])
Create a memory-map to an array stored in a binary file on disk.
lib.format.open_memmap(filename[, mode, ...])
Open a .npy file as a memory-mapped array.
Text formatting options# Base-n representations#binary_repr(num[, width])
Return the binary representation of the input number as a string.
base_repr(number[, base, padding])
Return a string representation of a number in the given base system.
Data sources# Binary format description#RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4