commit 61a8ff2238d51d505157072cd924e46141fd80bc
author Haonan <hhaonan@outlook.com> Thu Aug 11 15:04:37 2022 +0800
committer GitHub <noreply@github.com> Thu Aug 11 15:04:37 2022 +0800
tree 1fb25ede9f126172ddf69ec54b2d89c76afd298e
parent 1b5d88b5e451bd93c1328753cc0692e6aa4e1982

[IOTDB-3801] Update doc about python numpy tablet (#6863)

client-py/README.md

diff --git a/client-py/README.md b/client-py/README.md
index beef55e..3197cc7 100644
--- a/client-py/README.md
+++ b/client-py/README.md
@@ -187,6 +187,7 @@
 (if not, the default dtypes are also ok).
 
 ```python
+import numpy as np
 data_types_ = [
     TSDataType.BOOLEAN,
     TSDataType.INT32,

docs/UserGuide/API/Programming-Python-Native-API.md

diff --git a/docs/UserGuide/API/Programming-Python-Native-API.md b/docs/UserGuide/API/Programming-Python-Native-API.md
index 0f962eb..971c3ba 100644
--- a/docs/UserGuide/API/Programming-Python-Native-API.md
+++ b/docs/UserGuide/API/Programming-Python-Native-API.md
@@ -165,6 +165,7 @@
    (if not, the default dtypes are also ok).
 
 ```python
+import numpy as np
 data_types_ = [
     TSDataType.BOOLEAN,
     TSDataType.INT32,
@@ -179,7 +180,7 @@
     np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
     np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
     np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
-    np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
+    np.array(["test01", "test02", "test03", "test04"]),
 ]
 np_timestamps_ = np.array([1, 2, 3, 4], TSDataType.INT64.np_dtype())
 np_tablet_ = NumpyTablet(

docs/zh/UserGuide/API/Programming-Python-Native-API.md

diff --git a/docs/zh/UserGuide/API/Programming-Python-Native-API.md b/docs/zh/UserGuide/API/Programming-Python-Native-API.md
index 9f38508..dbda869 100644
--- a/docs/zh/UserGuide/API/Programming-Python-Native-API.md
+++ b/docs/zh/UserGuide/API/Programming-Python-Native-API.md
@@ -161,9 +161,10 @@
 
 **注意**
 1. Tablet 中的每一列时间戳和值记录为一个 ndarray
-2. ndarray 推荐使用如下面例子中的特定的 dtype，如果不使用，不会影响正确性。
+2. Numpy Tablet 只支持大端类型数据，ndarray 构建时如果不指定数据类型会使用小端，因此推荐在构建 ndarray 时指定下面例子中类型使用大端。如果不指定，IoTDB Python客户端也会进行大小端转换，不影响使用正确性。
 
 ```python
+import numpy as np
 data_types_ = [
     TSDataType.BOOLEAN,
     TSDataType.INT32,
@@ -178,7 +179,7 @@
     np.array([11, 11111, 1, 0], TSDataType.INT64.np_dtype()),
     np.array([1.1, 1.25, 188.1, 0], TSDataType.FLOAT.np_dtype()),
     np.array([10011.1, 101.0, 688.25, 6.25], TSDataType.DOUBLE.np_dtype()),
-    np.array(["test01", "test02", "test03", "test04"], TSDataType.TEXT.np_dtype()),
+    np.array(["test01", "test02", "test03", "test04"]),
 ]
 np_timestamps_ = np.array([1, 2, 3, 4], TSDataType.INT64.np_dtype())
 np_tablet_ = NumpyTablet(