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I am trying to convert a named list of lists to a dataframe using tidy functions, such as those available in `purrr`

. I tried solutions from here and here, but neither of them work for me (e.g., rows are not single observations). Also, neither option provided a solution on how to keep the object(?) names (e.g., e1m1_fit and e2m2a_fit) associated with the new rows in the dataframe.

```
library("tidyverse")
# The named list I am trying to convert to a dataframe/tibble:
df <-
list(e1m1_fit = structure(list(term = c("(Intercept)", "log10(q)"),
estimate = c(2.7, -0.1), std.error = c(0.03, 0.01),
statistic = c(88.04, -15.55),
p.value = c(0.01, 0.01)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -2L)),
e2m2a_fit = structure(list(term = c("(Intercept)", "log10(q)"),
estimate = c(2.7, -0.1),
std.error = c(0.03, 0.01),
statistic = c(79.78, -15.48),
p.value = c(0.01, 0.01)),
class = c("tbl_df", "tbl", "data.frame"),
row.names = c(NA, -2L)))
# I tried a solution like this, but a) it's not generalized/it's very specific to this example.
# And I cannot figure out how to associate the correct parameter/coefficient estimate with the correct value (they all end up in the same row).
# Also, it does not pass along the object name (e.g., e1m1_fit) to the new dataframe/tibble.
# A solution I tried that doesn't accomplish what I want:
df2 <-
df %>%
tibble(term = map(., "term"),
estimate = map(., "estimate"),
std_error = map(., "std.error"),
statistic = map(., "statistic"),
p_val = map(., "p.value")
) %>%
mutate(term1 = map_chr(term, 1),
term2 = map_chr(term, 2),
estimate1 = map_dbl(estimate, 1),
estimate2 = map_dbl(estimate, 2))
```

Any help is greatly appreciated!

### >Solution :

We may use `bind_rows`

which have the `.id`

that creates a new column from the `names`

of the `list`

```
library(dplyr)
bind_rows(df, .id = "fitname")
# A tibble: 4 × 6
fitname term estimate std.error statistic p.value
<chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 e1m1_fit (Intercept) 2.7 0.03 88.0 0.01
2 e1m1_fit log10(q) -0.1 0.01 -15.6 0.01
3 e2m2a_fit (Intercept) 2.7 0.03 79.8 0.01
4 e2m2a_fit log10(q) -0.1 0.01 -15.5 0.01
```

In addition, if the `df`

`list`

was created by looping with `map`

, the `_dfr`

can return a single `tibble/data.frame`

with the `.id`

specified as the name of the `list`

```
library(purrr)
map_dfr(yourlist, ~ yourfun(.x), .id = "fitname")
```