1.下载MongoDB 官网下载:https://www.mongodb.com/download-center#community 上面这张图选择第二个按钮 上面这张图直接Next 把bin路径添加到path中,如下图: 在安装路径下自己创建一个文件mongo.conf,配置内容如下: #数据库路径dbpath=E:\mongodb\data#日志输出文件路径logpath=E:\mongodb\log\mongo.log#错误日志采用追加模式logappend=true#启用日志文件,默认启…

import glob import os.path import numpy as np import tensorflow as tf from tensorflow.python.platform import gfile import tensorflow.contrib.slim as slim # 加载通过TensorFlow-Slim定义好的inception_v3模型. import tensorflow.contrib.slim.python.slim.nets.incepti…

import pandas as pd # Data analysis import numpy as np #Data analysis import seaborn as sns # Data visualization import matplotlib.pyplot as plt # Data Visualization import matplotlib.gridspec as gridspec # subplots and grid from wordcloud import Wor…

# This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load in import numpy as np…

# This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load in import matplotlib.p…

df = pd.read_csv("F:\\kaggleDataSet\\chennai-water\\chennai_reservoir_levels.csv") df["Date"] = pd.to_datetime(df["Date"], format='%d-%m-%Y') df.head() import datetime def scatter_plot(cnt_srs, color): trace = go.Scatter( x=c…

# This Python 3 environment comes with many helpful analytics libraries installed # It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python # For example, here's several helpful packages to load in import numpy as np…

# import pandas import pandas as pd # creating a DataFrame pd.DataFrame({'Yes': [50, 31], 'No': [101, 2]}) # another example of creating a dataframe pd.DataFrame({'Bob': ['I liked it.', 'It was awful.'], 'Sue': ['Pretty good.', 'Bland']}) pd.DataFram…

import numpy as np import pandas as pd import os import matplotlib.pyplot as pl import seaborn as sns import warnings warnings.filterwarnings('ignore') data = pd.read_csv('F:\\kaggleDataSet\\MedicalCostPersonal\\insurance.csv') data.head() data.isnul…

import os import numpy as np import pandas as pd from datetime import datetime import matplotlib import matplotlib.pyplot as plt import seaborn as sns sns.set_style('white') %matplotlib inline %load_ext autoreload %autoreload 2 def to_utms(ut): retur…