scale

问题 I am trying to plot 3 lines using geom_line() in my ggplot graph. One of the variables has a different scale so I am trying to use the sec.axis in order to show it as well. library(ggplot2) library(reshape2) tab <- data.frame(year = seq(1979,2010), freq = runif(32, 212,283), max = runif(32, 962.1, 993.4), med = runif(32, 972.1, 989.3), min = runif(32, 955.7, 978.3)) summary(tab) # the column freq (frequency) has a different scale comparing with the other ones Some code I've tried. tab <- melt

问题 I'm using this code to plot a map of temperature change in North America: ggplot(maps, aes(y=Latitude, x=Longitude, z=variable)) + ggtitle(title)+ scale_fill_brewer(palette = "Spectral")+ geom_contour_filled(breaks = c(-Inf,-2., -1.5, -1., -0.5, 0, 0.5, 1, 1.5, 2, 3, 4, 5, 7, 9, 11,Inf))+ xlim(-146,-44)+ ylim(35,90)+ theme(plot.title = element_text(hjust = 0.5)) And I want to change the color palette for better visualization. Currently, it writes scale_fill_brewer(palette = "Spectral") , and

问题 I'm using this code to plot a map of temperature change in North America: ggplot(maps, aes(y=Latitude, x=Longitude, z=variable)) + ggtitle(title)+ scale_fill_brewer(palette = "Spectral")+ geom_contour_filled(breaks = c(-Inf,-2., -1.5, -1., -0.5, 0, 0.5, 1, 1.5, 2, 3, 4, 5, 7, 9, 11,Inf))+ xlim(-146,-44)+ ylim(35,90)+ theme(plot.title = element_text(hjust = 0.5)) And I want to change the color palette for better visualization. Currently, it writes scale_fill_brewer(palette = "Spectral") , and

问题 I'm using this code to plot a map of temperature change in North America: ggplot(maps, aes(y=Latitude, x=Longitude, z=variable)) + ggtitle(title)+ scale_fill_brewer(palette = "Spectral")+ geom_contour_filled(breaks = c(-Inf,-2., -1.5, -1., -0.5, 0, 0.5, 1, 1.5, 2, 3, 4, 5, 7, 9, 11,Inf))+ xlim(-146,-44)+ ylim(35,90)+ theme(plot.title = element_text(hjust = 0.5)) And I want to change the color palette for better visualization. Currently, it writes scale_fill_brewer(palette = "Spectral") , and

问题 i have a problem with scale transforme effect and overflow on Safari. When i used this effect on a div content, the overflow not work on a rounded container. here my code: .container{ width:100px; height:100px; border-radius: 50%; background:none; z-index:100; box-shadow: inset 0 0 0 6px rgba(255,255,255,0.6), 0 1px 2px rgba(0,0,0,0.1); overflow:hidden; -webkit-transition:all .9s ease-in-out; // Chrome Safari -moz-transition:all.9s ease-in-out; // Mozilla -o-transition:all.9s ease-in-out; //

问题 i have a problem with scale transforme effect and overflow on Safari. When i used this effect on a div content, the overflow not work on a rounded container. here my code: .container{ width:100px; height:100px; border-radius: 50%; background:none; z-index:100; box-shadow: inset 0 0 0 6px rgba(255,255,255,0.6), 0 1px 2px rgba(0,0,0,0.1); overflow:hidden; -webkit-transition:all .9s ease-in-out; // Chrome Safari -moz-transition:all.9s ease-in-out; // Mozilla -o-transition:all.9s ease-in-out; //

问题 i have a problem with scale transforme effect and overflow on Safari. When i used this effect on a div content, the overflow not work on a rounded container. here my code: .container{ width:100px; height:100px; border-radius: 50%; background:none; z-index:100; box-shadow: inset 0 0 0 6px rgba(255,255,255,0.6), 0 1px 2px rgba(0,0,0,0.1); overflow:hidden; -webkit-transition:all .9s ease-in-out; // Chrome Safari -moz-transition:all.9s ease-in-out; // Mozilla -o-transition:all.9s ease-in-out; //

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,