014.ningxueTimePlot.ipynb

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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!/usr/bin/env python\n",
    "# -*- encoding: utf-8 -*-\n",
    "'''\n",
    "@文件        :014.ningxueTimePlot.ipynb\n",
    "@说明        : plot the bar chart of ningxue's time\n",
    "@时间        :2023/04/24 21:06:34\n",
    "@作者        :Wu Baosheng\n",
    "@版本        :1.0\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import os,re,sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scanpy.external as sce\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import tspex\n",
    "import plotly.express as px\n",
    "import plotly.io as pio\n",
    "mpl.rcParams['pdf.fonttype'] = 42\n",
    "mpl.rcParams['ps.fonttype'] = 42\n",
    "# sns.set(style='white', font_scale=1)\n",
    "# %config InlineBackend.figure_format = 'svg'\n",
    "cmap = sns.blend_palette(['#5F6F94','#FFFAFA','#DD5353'],as_cmap=True)   ##4C6793\n",
    "os.chdir('H:/002.singcell/01.liver/10.mutileSpecies/05.SAMap/07.Heps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "### read excel\n",
    "df = pd.read_excel('./凝血时间.xlsx',sheet_name='APTT',engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>human</th>\n",
       "      <th>rat</th>\n",
       "      <th>chicken</th>\n",
       "      <th>lizard</th>\n",
       "      <th>frog</th>\n",
       "      <th>Pagrus_pagrus</th>\n",
       "      <th>Dicentrarchus_labrax</th>\n",
       "      <th>Dentex_dentex</th>\n",
       "      <th>Sparus_auratus</th>\n",
       "      <th>crap</th>\n",
       "      <th>lungfish</th>\n",
       "      <th>dogshark</th>\n",
       "      <th>lamprey</th>\n",
       "      <th>hagfish</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>26.50</td>\n",
       "      <td>19.0</td>\n",
       "      <td>27.9</td>\n",
       "      <td>36.0</td>\n",
       "      <td>21.0</td>\n",
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       "      <td>35.0</td>\n",
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       "      <td>48.0</td>\n",
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       "      <th>4</th>\n",
       "      <td>31.01</td>\n",
       "      <td>26.0</td>\n",
       "      <td>28.7</td>\n",
       "      <td>40.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>32.28</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.0</td>\n",
       "      <td>37.0</td>\n",
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       "      <th>6</th>\n",
       "      <td>27.90</td>\n",
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       "      <td>29.60</td>\n",
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       "      <td>29.80</td>\n",
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       "   human   rat  chicken  lizard  frog  Pagrus_pagrus  Dicentrarchus_labrax  \\\n",
       "0  26.50  19.0     27.9    36.0  21.0           25.0                  26.0   \n",
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       "3  30.46  24.0     28.2    41.0  22.0            NaN                   NaN   \n",
       "4  31.01  26.0     28.7    40.0  19.0            NaN                   NaN   \n",
       "5  32.28   NaN      NaN     NaN   NaN            NaN                   NaN   \n",
       "6  27.90   NaN      NaN     NaN   NaN            NaN                   NaN   \n",
       "7  29.60   NaN      NaN     NaN   NaN            NaN                   NaN   \n",
       "8  29.80   NaN      NaN     NaN   NaN            NaN                   NaN   \n",
       "\n",
       "   Dentex_dentex  Sparus_auratus  crap  lungfish  dogshark  lamprey  hagfish  \n",
       "0           58.5            47.0  37.0      36.0     100.0    120.0    108.0  \n",
       "1            NaN             NaN  35.0      38.0      98.0      NaN    103.0  \n",
       "2            NaN             NaN  48.0      41.0     105.0      NaN    104.0  \n",
       "3            NaN             NaN  46.0      35.0     102.0      NaN    107.0  \n",
       "4            NaN             NaN  44.0      33.0       NaN      NaN      NaN  \n",
       "5            NaN             NaN  44.0      37.0       NaN      NaN      NaN  \n",
       "6            NaN             NaN   NaN       NaN       NaN      NaN      NaN  \n",
       "7            NaN             NaN   NaN       NaN       NaN      NaN      NaN  \n",
       "8            NaN             NaN   NaN       NaN       NaN      NaN      NaN  "
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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    "df"
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  {
   "cell_type": "code",
   "execution_count": 4,
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   "outputs": [],
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    "df=df[['hagfish','lamprey','dogshark','crap','Pagrus_pagrus','Dicentrarchus_labrax','Dentex_dentex','Sparus_auratus','lungfish','frog','lizard','chicken','rat','human']]"
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           "ticks": "",
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   ],
   "source": [
    "### express 绘制柱状图，带有误差棒\n",
    "fig = px.bar(df.mean(axis=0),error_y=df.std(axis=0),labels={'x':'species','y':'APTT'},color_discrete_sequence=['#5F6F94','#FFFAFA','#DD5353'])\n",
    "fig.show()\n",
    "pio.write_image(fig,'./APTT.pdf')"
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  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
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  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "index"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "value"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### express 绘制柱状图，带有误差棒\n",
    "fig1 = px.bar(df1.mean(axis=0),error_y=df1.std(axis=0),labels={'x':'species','y':'APTT'},color_discrete_sequence=['#5F6F94','#FFFAFA','#DD5353'])\n",
    "fig1.show()\n",
    "fig1.write_image('./PT.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=-9.927003349467073, pvalue=3.8761260401106515e-07)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#### 计算各个物种的凝血时间的差异的p值\n",
    "from scipy.stats import ttest_ind\n",
    "ttest_ind(df.mean(axis=0).to_list()[3: ],df.mean(axis=0).to_list()[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[42.333333333333336,\n",
       " 25.0,\n",
       " 26.0,\n",
       " 58.5,\n",
       " 47.0,\n",
       " 36.666666666666664,\n",
       " 19.4,\n",
       " 39.0,\n",
       " 28.7,\n",
       " 22.0,\n",
       " 30.444444444444443]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean(axis=0).to_list()[2: ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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