历史文章附件列表/（数据科学学习手札91）在Python中妥善使用进度条/（数据科学学习手札91）在Python中妥善使用进度条.ipynb

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   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 利用tqdm玩转进度条"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1 基础用法"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **tqdm.tqdm**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
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     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:02<00:00,  4.94it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "import time\n",
    "\n",
    "for i in tqdm(range(10)):\n",
    "    \n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **配合列表推导**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:02<00:00,  4.96it/s]\n"
     ]
    }
   ],
   "source": [
    "temp = [time.sleep(0.2) for i in tqdm(range(10))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **trange**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:02<00:00,  4.98it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import trange\n",
    "\n",
    "for i in trange(10):\n",
    "    \n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **desc说明文字**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "这是一个进度条: 100%|██████████████████████████████████████████████████████████████████| 10/10 [00:02<00:00,  4.97it/s]\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(10), desc='这是一个进度条'):\n",
    "    \n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **实时修改说明文字**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-07-31T10:02:18.469994Z",
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "第9轮: 100%|███████████████████████████████████████████████████████████████████████████| 10/10 [00:02<00:00,  4.95it/s]  \n"
     ]
    }
   ],
   "source": [
    "bar = tqdm(range(10))\n",
    "for i in bar:\n",
    "    time.sleep(0.2)\n",
    "    bar.set_description(f'第{i}轮')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **对字典进行迭代**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-07-31T10:02:20.496572Z",
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "10it [00:02,  4.96it/s]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({'a': range(10)})\n",
    "\n",
    "for row in tqdm(df.itertuples()):\n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2 配合jupyter notebook/jupyter lab的美观进度条"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-07-31T10:02:22.785450Z",
     "iopub.status.busy": "2020-07-31T10:02:22.785450Z",
     "iopub.status.idle": "2020-07-31T10:02:24.859993Z",
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     "shell.execute_reply.started": "2020-07-31T10:02:22.785450Z"
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       "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))"
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     },
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from tqdm.notebook import trange\n",
    "\n",
    "for i in trange(10):\n",
    "    \n",
    "    time.sleep(0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3 配合pandas中的apply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
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    },
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     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from tqdm.notebook import tqdm\n",
    "\n",
    "tqdm.pandas(desc='pandas专属进度条')\n",
    "_ = df.progress_apply(lambda _: time.sleep(0.2), axis=1)"
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