dataframe 相关问题

数据框是表格数据结构。通常，它包含数据，其中行是观察值，列是各种类型的变量。虽然“数据框架”或“数据框架”是这个概念用于多种语言的术语（R，Apache Spark，deedle，Maple，Python中的pandas库和Julia中的DataFrames库），“table”是用于的术语MATLAB和SQL。

如何映射具有多个参数（和更改数据）的函数？

我正在创建一个函数，为州-城市级别的数据框中的各个州创建 gt 表。我会经常更改数据以及 gt 中选定的列，因此我添加...

r dataframe purrr gt

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如何根据另一个列值指定带后缀的列名

#X 列包含 V* 列之一的后缀。需要将 V(X) 中的值放入 Y 列中。将 pandas 导入为 pd 将 numpy 导入为 np # 示例数据帧 df = pd.DataFrame({ 'EMPLID'：[12，...

python dataframe

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根据字符串条件将数据帧行扩展为多行

我有一些类似于下面的数据框的原始数据： df = pd.DataFrame([{'var1': '220-224（偶数）路名1', 'var2': '位置1', 'var3': '区域1'}, {'var1': '5 到 9 的站点（o...

python pandas string dataframe expand

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将前一行中 2 个单元格的值添加到数据框中的当前行

我有一个如下所示的数据框名称值 =================== 一个2400 乙-400 C 400 d 600 我需要 df 采用以下格式名称 Lower_V...

python python-3.x pandas dataframe

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为连接两个Python数据框的资源分配订单

我有一个数据框问题。我有两个数据框。第一个数据帧包含订单详细信息，第二个数据帧包含线圈详细信息。我需要给线圈分配订单以满足订单的需求...

python pandas dataframe

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为什么决定让 data.table 和 tibble 与 R 中的 data.frame 不兼容？ [已关闭]

我使用 R 已有多年，有时会遇到由于 data.table 和 tibble 与 data.frame 不兼容而导致的问题。这通常需要在它们之间执行转换...

r dataframe data.table tidyverse tibble

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Databricks DLT DataFrame - 如何使用带有注释的模式

Databricks DLT DataFrame - 如何使用模式我是 Databricks Delta Live Tables 和 DataFrames 的新手，我对阅读时如何使用模式感到困惑从溪流中。我正在逐桌做

dataframe azure-databricks databricks-sql delta-live-tables

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从数据表的列中选择数据

比如说我的数据是：年份车门气缸传动装置 2003 日产 4 4 吨 2006 日产 4 4 吨 2003 本田 2 6 AT 我要闪亮归还f...

r dataframe

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使用 R 中的 ggplot 2 合并条形图中的条形

我有一个名为 df 的数据框，它有 3 个 Likert 量表级别列和一个过滤器列： df # 小标题：50 × 4 val1 val2 val3 var 我有一个名为 df 的数据框，它有 3 个 Likert 量表级别列和一个过滤器列： df # A tibble: 50 × 4 val1 val2 val3 var <chr> <chr> <chr> <chr> 1 "Very \n Dissatisfied" "Neutral" "Very \n Dissatisf… Yes 2 "Neutral" "Neutral" "Neutral" No 3 "Dissatisfied" "Satisfied" "Neutral" Yes 4 "Very \n Satisfied" "Satisfied" "Very \n Satisfied" Yes 5 "Very \n Dissatisfied" "Very \n Dissatisfied" "Neutral" Yes 6 "Very \n Satisfied" "Very \n Satisfied" "Very \n Satisfied" Yes 7 "Dissatisfied" "Neutral" "Dissatisfied" Yes 8 "Neutral" "Satisfied" "Neutral" Yes 9 "Satisfied" "Very \n Satisfied" "Satisfied" No 10 "Neutral" "Satisfied" "Neutral" Yes 上一个问题的结果函数这里给了我所有相同值的条形图。这是正确的。！！我想要的只是不要重复 3 次（20,30 和 50），我想在右图的这一栏上重复一次。不是 3 次。这可能吗？ plot_fun <- function(x, y) { .data <- df |> filter(var %in% x) p1 <- .data |> ggstats::gglikert(include = -var) + aes(y = reorder(.question, ifelse( .answer %in% c("Very \n Dissatisfied", "Dissatisfied"), 1, 0 ), FUN = sum ), decreasing = TRUE) + facet_wrap(~paste0("var to ", y))+ scale_fill_manual(values = custom_colors) + theme( strip.text = element_text(size = 14,color = "black"), # Increase facet label size axis.title = element_text(size = 14), # Increase axis title size axis.text = element_text(size = 10))+ # Increase axis text size theme(strip.background = element_rect(color="black", fill="red", size=1.5, linetype="solid")) p2 <- .data %>% tidyr::pivot_longer(-var) |> filter(!is.na(value)) |> mutate( name = reorder(name, ifelse( value %in% c("Very \n Dissatisfied", "Dissatisfied"), 1, 0 ), FUN = sum ) ) |> ggplot(aes(y = name)) + geom_bar(fill = "lightgrey")+ theme_light()+ geom_text(aes(label = ..count..), stat = "count", position=position_stack(vjust = 0.5))+ theme( axis.text.y = element_blank(), axis.ticks.y = element_blank()) list(p1, p2) } .include <- list(No = "No", Yes = "Yes", All = c("Yes", "No")) purrr::imap(.include, plot_fun) |> purrr::reduce(c) |> wrap_plots(ncol = 2) + plot_layout(axes = "collect", guides = "collect", widths = c(.7, .3)) & labs(x = NULL, y = NULL) & theme(legend.position = "bottom") 数据 dput(df) structure(list(val1 = c("Very \n Dissatisfied", "Neutral", "Dissatisfied", "Very \n Satisfied", "Very \n Dissatisfied", "Very \n Satisfied", "Dissatisfied", "Neutral", "Satisfied", "Neutral", "Very \n Dissatisfied", "Very \n Satisfied", "Very \n Dissatisfied", "Satisfied", "Neutral", "Very \n Dissatisfied", "Neutral", "Neutral", "Satisfied", "Neutral", "Very \n Satisfied", "Dissatisfied", "Dissatisfied", "Satisfied", "Neutral", "Dissatisfied", "Satisfied", "Very \n Dissatisfied", "Dissatisfied", "Very \n Dissatisfied", "Very \n Dissatisfied", "Dissatisfied", "Dissatisfied", "Dissatisfied", "Neutral", "Dissatisfied", "Dissatisfied", "Very \n Dissatisfied", "Satisfied", "Satisfied", "Neutral", "Very \n Dissatisfied", "Very \n Satisfied", "Very \n Dissatisfied", "Satisfied", "Very \n Dissatisfied", "Very \n Dissatisfied", "Satisfied", "Dissatisfied", "Dissatisfied"), val2 = c("Neutral", "Neutral", "Satisfied", "Satisfied", "Very \n Dissatisfied", "Very \n Satisfied", "Neutral", "Satisfied", "Very \n Satisfied", "Satisfied", "Very \n Dissatisfied", "Very \n Satisfied", "Satisfied", "Very \n Satisfied", "Satisfied", "Neutral", "Dissatisfied", "Satisfied", "Neutral", "Satisfied", "Satisfied", "Neutral", "Very \n Satisfied", "Very \n Satisfied", "Satisfied", "Satisfied", "Very \n Satisfied", "Satisfied", "Neutral", "Neutral", "Neutral", "Neutral", "Neutral", "Satisfied", "Satisfied", "Dissatisfied", "Neutral", "Satisfied", "Very \n Satisfied", "Satisfied", "Satisfied", "Very \n Dissatisfied", "Satisfied", "Neutral", "Satisfied", "Very \n Dissatisfied", "Neutral", "Satisfied", "Neutral", "Satisfied" ), val3 = c("Very \n Dissatisfied", "Neutral", "Neutral", "Very \n Satisfied", "Neutral", "Very \n Satisfied", "Dissatisfied", "Neutral", "Satisfied", "Neutral", "Very \n Dissatisfied", "Very \n Satisfied", "Very \n Dissatisfied", "Satisfied", "Neutral", "Very \n Dissatisfied", "Satisfied", "Neutral", "Satisfied", "Neutral", "Very \n Satisfied", "Neutral", "Satisfied", "Satisfied", "Neutral", "Dissatisfied", "Satisfied", "Very \n Satisfied", "Neutral", "Very \n Dissatisfied", "Very \n Dissatisfied", "Dissatisfied", "Satisfied", "Dissatisfied", "Dissatisfied", "Very \n Dissatisfied", "Dissatisfied", "Very \n Dissatisfied", "Satisfied", "Satisfied", "Neutral", "Very \n Dissatisfied", "Very \n Satisfied", "Very \n Dissatisfied", "Satisfied", "Very \n Dissatisfied", "Dissatisfied", "Satisfied", "Neutral", "Dissatisfied"), var = c("Yes", "No", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "No", "Yes", "No", "No", "Yes", "No", "No", "No", "No", "No", "Yes", "No", "No", "Yes", "No", "No", "No", "Yes", "No", "No", "Yes", "No", "No", "No", "No", "No", "Yes", "No", "No", "No", "Yes", "No", "No", "Yes", "Yes", "No", "Yes", "Yes", "No", "No", "No", "Yes" )), row.names = c(NA, -50L), class = c("tbl_df", "tbl", "data.frame" )) likert_levels <- c( "Strongly disagree", "Disagree", "Neither agree nor disagree", "Agree", "Strongly agree" ) 只需拆下枢轴部分即可： library(tidyverse) library(patchwork) likert_levels <- c( "Very \n Dissatisfied", "Dissatisfied", "Neutral", "Satisfied", "Very \n Satisfied" ) plot_fun <- function(x, y) { .data <- df |> filter(var %in% x) |> mutate( across(-var, ~ factor(.x, likert_levels)) ) p1 <- .data |> ggstats::gglikert(include = -var) + aes(y = reorder(.question, ifelse( .answer %in% c("Very \n Dissatisfied", "Dissatisfied"), 1, 0 ), FUN = sum ), decreasing = TRUE) + facet_wrap(~ paste0("var to ", y)) + # scale_fill_manual(values = custom_colors) + theme( strip.text = element_text(size = 14, color = "black"), # Increase facet label size axis.title = element_text(size = 14), # Increase axis title size axis.text = element_text(size = 10) ) + # Increase axis text size theme(strip.background = element_rect(color = "black", fill = "red", size = 1.5, linetype = "solid")) p2 <- .data %>% count() |> ggplot(aes(y = factor(1), x = n)) + geom_col(fill = "lightgrey") + theme_light() + geom_text(aes(label = n), position = position_stack(vjust = 0.5) ) + theme( axis.text.y = element_blank(), axis.ticks.y = element_blank() ) list(p1, p2) } .include <- list(No = "No", Yes = "Yes", All = c("Yes", "No")) purrr::imap(.include, plot_fun) |> purrr::reduce(c) |> wrap_plots(ncol = 2) + plot_layout(guides = "collect", widths = c(.7, .3)) & labs(x = NULL, y = NULL) & theme(legend.position = "bottom")

r dataframe ggplot2 likert

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如何创建基于pandas（python）中其他2个DataFrame的最小值的DataFrame？

假设我有 DataFrame df1 和 df2： >>> df1 = pd.DataFrame({'A': [0, 2, 4], 'B': [2, 17, 7], 'C': [4, 9, 11]}) >>> df1 ABC 0 0 2 4 1 2 17 9 2 4 7 11 >...

python pandas dataframe min

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根据日期持续时间绘制关卡花费的时间 pandas python

我有这个数据集，其中包含给定时间内问题发生情况的日志。我想标记每个状态，表明它在那段时间达到了什么水平。我在 python 上做的...

python pandas dataframe

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多个数据帧并尝试在它们上使用 PCA

我有三个数据帧（不同的变量），我试图在 python 中运行 PCA。它们的尺寸为： df1 = 17行×60212列（17是模型名称，60212是数据） df2 =...