timeserieschart

问题 I am trying to do analysis on a bike share dataset. Part of the analysis includes showing the weekends' demand in date wise plot. My dataframe in pandas with last 5 row looks like this. Here is my code for date vs total ride plot. import seaborn as sns sns.set_style("darkgrid") plt.plot(d17_day_count) plt.show() . I want to highlight weekends in the plot. So that it could look something similar to this plot. I am using Python with matplotlib and seaborn library. 回答1: You can easily highlight

问题 Take the following straightforward plot of two time series from the economics{ggplot2} dataset require(dplyr) require(ggplot2) require(lubridate) require(tidyr) economics %>% gather(indicator, percentage, c(4:5), -c(1:3, 6)) %>% mutate(Y2K = year(date) >= 2000) %>% group_by(indicator, Y2K) %>% ggplot(aes(date, percentage, group = indicator, colour = indicator)) + geom_line(size=1) I would like to change the linetype from "solid" to "dashed" (and possibly also the line size ) for all points in

问题 I have the following code (although without data, sadly): detrend_plot <- cbind(l_p_lng,l_vol_lng,l_p_oil,l_rgdpe, ldiff_p_lng,ldiff_vol_lng,ldiff_p_oil,ldiff_rgdpe) plot.ts(detrend_plot, main="",) which gives the following plot: What I want to do is to add custom titles, individual y-axis labels, and x-axis labels. I know that this is possible using GGPLOT , although my knowledge of it is sparse. Has anyone encountered a similar problem? I don't think this is possible using the regular plot

问题 I have a time series of several years that I need to plot mm/dd on the x-axis and multiple years on the y-axis using plot_ly. I have generated a sample data here: date<-seq(as.Date("2010-11-22"),as.Date("2016-05-26"),by ="days") sales = runif(2013, 2000, 6000) df = data.frame(date,sales) I plotted this data and get this: plot_ly(df,x= ~date) %>% add_lines(y = ~sales,color=I("red")) Now, I tried to plot multiple y-axis using plot_ly : plot_ly(df, x = ~date) %>% add_lines(y = ~sales, df$date <=

问题 I have a plotly graph of the EUR/JPY exchange rate across a few months in 15 minute time intervals, so as a result, there is no data from friday evenings to sunday evenings. Here is a portion of the data, note the skip in the index (type: DatetimeIndex) over the weekend: Plotting this data in plotly results in a gap over the missing dates Using the dataframe above: import plotly.graph_objs as go candlesticks = go.Candlestick(x=data.index, open=data['Open'], high=data['High'], low=data['Low'],

问题 I have been trying to plot time series data in R. I consulted several different sources online and somehow I am still having problems creating this plots. I have simulated some data below that represents daily information a fictitious company received from 2014 to 2016: #create data date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day") date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d") property_damages_in_dollars <- rnorm(731,100,10) car_damages_in

来源： https://stackoverflow.com/questions/63421569/making-a-timeseries-plot-in-python-but-want-to-skip-few-months

问题 I'm trying to plot a two "y" axis, the first one with "soil water content" in % (geom_line() ) and a geom_bar() with precipitation data. The problem is the precipitation chart. I need to "reverse" the plot. I have this chart now: and I need the soil water content time series as image above but precipitation as following image Transforming the data do not solve the problem since i can not transform the bar plot for visualize it form upside down since the data are bars not points. Overmore when

问题 I have a dataframe that records concentrations for several different locations in different years, with a high temporal frequency (<1 hour). I am trying to make a bar/multibar plot showing mean concentrations, at different locations in different years To calculate mean concentration, I have to apply quality control filters to daily and monthly data. My approach is to first apply filters and resample per year and then do the grouping by location and year. Also, out of all the locations (in the

问题 I have a dataframe that records concentrations for several different locations in different years, with a high temporal frequency (<1 hour). I am trying to make a bar/multibar plot showing mean concentrations, at different locations in different years To calculate mean concentration, I have to apply quality control filters to daily and monthly data. My approach is to first apply filters and resample per year and then do the grouping by location and year. Also, out of all the locations (in the