data-science

问题 I created a dataset with 6 clusters and visualize it with the code below, and find the cluster center points for every iteration, now i want to visualize demonstration of update of the cluster centroids in KMeans algorithm. This demonstration should include first four iterations by generating 2×2-axis figure. I found the points but i cant plot them, can you please check out my code and by looking that, help me write the algorithm to scatter plot? Here is my code so far: import seaborn as sns

问题 I created a dataset with 6 clusters and visualize it with the code below, and find the cluster center points for every iteration, now i want to visualize demonstration of update of the cluster centroids in KMeans algorithm. This demonstration should include first four iterations by generating 2×2-axis figure. I found the points but i cant plot them, can you please check out my code and by looking that, help me write the algorithm to scatter plot? Here is my code so far: import seaborn as sns

问题 I have a dataframe which looks like this. id YearReleased Artist count 168 2015 Muse 1 169 2015 Rihanna 3 170 2015 Taylor Swift 2 171 2016 Jennifer Lopez 1 172 2016 Rihanna 3 173 2016 Underworld 1 174 2017 Coldplay 1 175 2017 Ed Sheeran 2 I want to get the maximum count for each year and then get the corresponding Artist name. Something like this: YearReleased Artist 2015 Rihanna 2016 Rihanna 2017 Ed Sheeran I have tried using a loop to iterate over the rows of the dataframe and create

问题 I have a dataframe which looks like this. id YearReleased Artist count 168 2015 Muse 1 169 2015 Rihanna 3 170 2015 Taylor Swift 2 171 2016 Jennifer Lopez 1 172 2016 Rihanna 3 173 2016 Underworld 1 174 2017 Coldplay 1 175 2017 Ed Sheeran 2 I want to get the maximum count for each year and then get the corresponding Artist name. Something like this: YearReleased Artist 2015 Rihanna 2016 Rihanna 2017 Ed Sheeran I have tried using a loop to iterate over the rows of the dataframe and create

问题 I want to use sklearn 's StandardScaler . Is it possible to apply it to some feature columns but not others? For instance, say my data is: data = pd.DataFrame({'Name' : [3, 4,6], 'Age' : [18, 92,98], 'Weight' : [68, 59,49]}) Age Name Weight 0 18 3 68 1 92 4 59 2 98 6 49 col_names = ['Name', 'Age', 'Weight'] features = data[col_names] I fit and transform the data scaler = StandardScaler().fit(features.values) features = scaler.transform(features.values) scaled_features = pd.DataFrame(features,

问题 I want to use sklearn 's StandardScaler . Is it possible to apply it to some feature columns but not others? For instance, say my data is: data = pd.DataFrame({'Name' : [3, 4,6], 'Age' : [18, 92,98], 'Weight' : [68, 59,49]}) Age Name Weight 0 18 3 68 1 92 4 59 2 98 6 49 col_names = ['Name', 'Age', 'Weight'] features = data[col_names] I fit and transform the data scaler = StandardScaler().fit(features.values) features = scaler.transform(features.values) scaled_features = pd.DataFrame(features,

问题 I want to use sklearn 's StandardScaler . Is it possible to apply it to some feature columns but not others? For instance, say my data is: data = pd.DataFrame({'Name' : [3, 4,6], 'Age' : [18, 92,98], 'Weight' : [68, 59,49]}) Age Name Weight 0 18 3 68 1 92 4 59 2 98 6 49 col_names = ['Name', 'Age', 'Weight'] features = data[col_names] I fit and transform the data scaler = StandardScaler().fit(features.values) features = scaler.transform(features.values) scaled_features = pd.DataFrame(features,

问题 I want to use sklearn 's StandardScaler . Is it possible to apply it to some feature columns but not others? For instance, say my data is: data = pd.DataFrame({'Name' : [3, 4,6], 'Age' : [18, 92,98], 'Weight' : [68, 59,49]}) Age Name Weight 0 18 3 68 1 92 4 59 2 98 6 49 col_names = ['Name', 'Age', 'Weight'] features = data[col_names] I fit and transform the data scaler = StandardScaler().fit(features.values) features = scaler.transform(features.values) scaled_features = pd.DataFrame(features,

问题 I am trying to accomplish something similar to what is here : https://www.opportunityatlas.org/. If you proceed further to this link and click on 'Show Distribution' to see the graph and select 'On Screen' and then move the cursor around the map you will see the size of the rectangles changes and also the update patterns works i.e. if a rectangle was already there it moves horizontally to the new value. I have tried doing the same but could not achieve the update part . Could you please point

问题 I am trying to accomplish something similar to what is here : https://www.opportunityatlas.org/. If you proceed further to this link and click on 'Show Distribution' to see the graph and select 'On Screen' and then move the cursor around the map you will see the size of the rectangles changes and also the update patterns works i.e. if a rectangle was already there it moves horizontally to the new value. I have tried doing the same but could not achieve the update part . Could you please point