How to deal with 'firm-country-year' type panel data

Question

I have a panel dataset with a 'Company Name - Country - Year' structure. The variables are financial attributes for listed companies (say, y, x1, x2 x3 etc.) located in different countries. There are 4 countries involved and the dataset spans 10 years (2011 to 2020). The number of companies for which data is available differs across the 4 countries.

Following is a snapshot of the dataset.

Company	Country	Year	D/E	TDTA	LTDTA	STDTA	Liquid ratio	Profitability	Size	P/E	Surplus
ALICON CASTALLOY LTD	India	2011	128.3589	0.371844392	0.155361798	0.216482594	0.626872695	0.143452963	21.88224644	3.6629	0.191703899
ALICON CASTALLOY LTD	India	2012	145.8856	0.361449015	0.075690176	0.285758839	0.632109096	0.121955491	22.26809975	4.6148	0.189898385
ALICON CASTALLOY LTD	India	2013	114.6795	0.32939055	0.016479674	0.312910876	0.597648987	0.110514887	22.38078659	3.6636	0.161800789
ALICON CASTALLOY LTD	India	2014	107.9006	0.318235519	0.032506572	0.285728947	0.622053575	0.11292846	22.39569031	4.8393	0.097195415
ALICON CASTALLOY LTD	India	2015	134.124	0.360167667	0.077957692	0.282209976	0.64851083	0.116692366	22.68836349	15.4823	0.284340355
ALICON CASTALLOY LTD	India	2016	138.4348	0.380129133	0.098677129	0.281452005	0.632704362	0.132214242	22.73671382	14.3018	0.261805373
ALICON CASTALLOY LTD	India	2017	153.7061	0.386036785	0.121818896	0.264217889	0.685974099	0.128421822	22.76660861	22.4139	0.114658603
ALICON CASTALLOY LTD	India	2018	106.3272	0.310354903	0.087852251	0.222502653	0.821700135	0.123780884	23.03925264	19.6087	0.091544136
ALICON CASTALLOY LTD	India	2019	91.0259	0.320969758	0.0801801	0.240789659	0.801445692	0.149648519	23.19887655	14.9046	0.190002201
ALICON CASTALLOY LTD	India	2020	106.5843	0.372381221	0.135538078	0.236843143	0.891019668	0.096605765	22.98210092	14.1902	0.099609827
AMARA RAJA BATTERIES LTD	India	2011	13.9508	0.080751313	0.06281992	0.017931393	1.213515068	0.202486795	23.59240034	10.9429	0.139951793
AMARA RAJA BATTERIES LTD	India	2012	10.21	0.062208615	0.058062164	0.004146452	1.629492248	0.222471791	23.88640399	11.6376	0.285242442

I want to perform a simple panel data analysis of the kind y ~ x1 + x2 + x3 using the plm package in R. Because of the 3-way structure I ran into difficulties so (as advised in Fixed Effects plm package R - multiple observations per year/id) I created a separate id for each company-country pair using dlpyr:

library(dplyr)
F1$id <- group_indices(F1, Company, Country)

where F1 is my input dataframe.

Now, when I run

library(plm)
formula = D_E ~ Liquidity_Ratio + Surplus 
plm.reg <- plm(formula, data = F1, index = c("id", "Year"), model = "between")
summary(plm.reg)

I am unable to understand the results (for eg. the summary is a long list of coeffs)

Call:
plm(formula = formula, data = F1, model = "between", index = c("id", 
    "Year"))

Unbalanced Panel: n = 552, T = 1-11, N = 3510
Observations used in estimation: 552

Residuals:
ALL 552 residuals are 0: no residual degrees of freedom!

Coefficients: (2959 dropped because of singularities)
                            Estimate Std. Error t-value Pr(>|t|)
(Intercept)                   0.1791        NaN     NaN      NaN
Liquidity_Ratio0.00450533    -0.1791        NaN     NaN      NaN
Liquidity_Ratio0.045110358   -0.7164        NaN     NaN      NaN
Liquidity_Ratio0.16995834   924.9422        NaN     NaN      NaN
Liquidity_Ratio0.172856618  376.0109        NaN     NaN      NaN
Liquidity_Ratio0.187658552  965.6439        NaN     NaN      NaN

and so on ending with

Liquidity_Ratio4.598641438   11.2690        NaN     NaN      NaN
Liquidity_Ratio4.856558476   -0.5373        NaN     NaN      NaN
Liquidity_Ratio5.593391052    7.4484        NaN     NaN      NaN
Liquidity_Ratio8.9001985      1.9260        NaN     NaN      Na
Total Sum of Squares:    3957000
Residual Sum of Squares: 0
R-Squared:      1
Adj. R-Squared: NaN
F-statistic: NaN on 551 and 0 DF, p-value: NA

I am new to panel data analysis and need to find out where I am going wrong.