Numpy data type is called dtype, in this tutorial, we will list some common used numpy data types, which is much richer than python standard data types.

Here is the list of basic numpy data types, you should notice data types with underscore (_) is identical to standard python types.

bool_ | Boolean, True or False. |

byte | One-byte signed integer. |

short | C-language short integer. |

intc | C-language int integer. |

int_ | Python int. |

int8, int16, int32 | Signed integers with 8, 16, and 32 bits respectively. |

longlong | Signed arbitrary-length integer. |

intp | An integer sized to hold a memory address. |

ubyte | Unsigned 8-bit integer. |

ushort | Unsigned C short. |

uintc | Unsigned C int. |

uint | Unsigned integer. |

uint8, uint16, uint32 | Unsigned integers of 8, 16, and 32 bits respectively. |

ulonglong | Unsigned arbitrary-length integer. |

uintp | Unsigned integer big enough to hold an address. |

single | Single-precision float. |

float_ | Python float. |

longfloat | Double-precision float. |

float32, float64 | Floats of 32 and 64 bits, respectively. |

csingle | Single-precision complex. |

complex_ | Python complex. |

clongfloat | Double-precision complex. |

object_ | For arrays of arbitrary Python objects. |

str_ | Eight-bit character string. |

unicode_ | Thirty-two-bit character string |

float32, float64 and int32 is commond used in many python applications.